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Overcoming Oversmoothness in Graph Convolutional Networks

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Here we propose to augment conventional GCNs with geometric scattering transforms and residual convolutions The former enables bandpass filtering of  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/hash/a6b964c0bb675116a15ef1325b01ff45-Abstract.html

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Learning Hierarchical Information Flow with Recurrent Neural

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Danijar Hafner Alexander Irpan James Davidson Nicolas Heess Abstract We propose ThalNet a deep learning model inspired by neocortical  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/7249-learning-hierarchical-information-flow-with-recurrent-neural-modules

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Bayesian Optimization with Robust NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Bayesian optimization is a prominent method for optimizing expensive to evaluate blackbox functions that is prominently applied to tuning the hyperparameters  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6117-bayesian-optimization-with-robust-bayesian-neural-networks

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Scalable Certified Defense against Adversarial Patches with

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Adversarial patch attacks that craft the pixels in a confined region of the input images show their powerful attack effectiveness in physical environments  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2021/hash/ed519c02f134f2cdd836cba387b6a3c8-Abstract.html

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The Limit Points of (Optimistic) Gradient Descent in MinMax

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Constantinos Daskalakis Ioannis Panageas Abstract Motivated by applications in Optimization Game Theory and the training of Generative  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8136-the-limit-points-of-optimistic-gradient-descent-in-min-max-optimization

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Discriminative Learning of SumProduct Networks NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Robert Gens Pedro Domingos Abstract Sumproduct networks are a new deep architecture that can perform fast exact in ference on hightreewidth  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/4516-discriminative-learning-of-sum-product-networks

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Blind source separation for overdetermined delayed mixtures

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Lars Omlor Martin Giese Abstract Blind source separation ie the extraction of unknown sources from a set of given signals is relevant for  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/3026-blind-source-separation-for-over-determined-delayed-mixtures

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Generating Sequential Data via Causal Optimal Transport

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

We introduce COTGAN an adversarial algorithm to train implicit generative mod els optimized for producing sequential data The loss function of this  - Information from papers.nips.cc

Information accuracy 100%
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Direct Loss Minimization for Structured Prediction NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Tamir Hazan Joseph Keshet David McAllester Abstract In discriminative machine learning one is interested in training a system to optimize a  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/4069-direct-loss-minimization-for-structured-prediction

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Identifying Representative Elements in Massive Data

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Baharan Mirzasoleiman Amin Karbasi Rik Sarkar Andreas Krause Abstract Many largescale machine learning problems (such as clustering  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/5039-distributed-submodular-maximization-identifying-representative-elements-in-massive-data

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SemiImplicit Graph Variational AutoEncoders NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Semiimplicit graph variational autoencoder (SIGVAE) is proposed to expand the flexibility of variational graph autoencoders (VGAE) to model graph data - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/9255-semi-implicit-graph-variational-auto-encoders

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Multivariate Time Series Imputation with Generative

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Multivariate Time Series Imputation with Generative Adversarial Networks A modified Gate Recurrent Unit is employed in GAN to model the temporal  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/7432-multivariate-time-series-imputation-with-generative-adversarial-networks

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A Probabilistic Framework for Deep Learning NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

We develop a probabilistic framework for deep learning based on the Deep Rendering Mixture Model (DRMM) a new generative probabilistic model that  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6231-a-probabilistic-framework-for-deep-learning

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On the Universality of Online Mirror Descent NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Nati Srebro Karthik Sridharan Ambuj Tewari Abstract We show that for a general class of convex online learning problems Mirror Descent can  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/4413-on-the-universality-of-online-mirror-descent

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SemiSeparable Hamiltonian Monte Carlo for Inference in

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Sampling from hierarchical Bayesian models is often difficult for MCMC methods Recent Riemannian manifold Hamiltonian Monte Carlo (RMHMC) methods have  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/5591-semi-separable-hamiltonian-monte-carlo-for-inference-in-bayesian-hierarchical-models

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Unsupervised Learning of Human Motion Models NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Yang Song Luis Goncalves Pietro Perona Abstract This paper presents an unsupervised learning algorithm that can derive the probabilistic  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2106-unsupervised-learning-of-human-motion-models

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Unifying CountBased Exploration and NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Unifying CountBased Exploration and Intrinsic Motivation Part of Advances in Neural Information Processing Systems 29 (NIPS 2016) - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6383-unifying-count-based-exploration-and-intrinsic-motivation

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Hierarchical Graph Representation Learning with

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Here we propose DiffPool a differentiable graph pooling module that can generate hierarchical representations of graphs and can be combined with various graph - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/7729-hierarchical-graph-representation-learning-with-differentiable-pooling

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Fault Diagnosis of Antenna Pointing Systems using Hybrid

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

The paper outlines our approach to building a monitoring system using hybrid signal processing and neural network techniques including autoregressive modelling  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/502-fault-diagnosis-of-antenna-pointing-systems-using-hybrid-neural-network-and-signal-processing-models

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MultiTask Learning via Conic Programming NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Tsuyoshi Kato Hisashi Kashima Masashi Sugiyama Kiyoshi Asai Abstract When we have several related tasks solving them simultaneously is shown  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/3368-multi-task-learning-via-conic-programming

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k*Nearest Neighbors: From Global to Local NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Oren Anava Kfir Levy Abstract The weighted knearest neighbors algorithm is one of the most fundamental nonparametric methods in pattern  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6373-k-nearest-neighbors-from-global-to-local

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Message Passing for Maxweight Independent Set NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Sujay Sanghavi Devavrat Shah Alan Willsky Abstract We investigate the use of messagepassing algorithms for the problem of finding the  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/3240-message-passing-for-max-weight-independent-set

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Exact Recovery of Corrupted LowRank Matrices via Convex

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

This paper considers the idealized “robust principal component analysis” problem of recovering a low rank matrix A from corrupted observations D A + E Here  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/3704-robust-principal-component-analysis-exact-recovery-of-corrupted-low-rank-matrices-via-convex-optimization

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Bayesian GAN NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Generative adversarial networks (GANs) can implicitly learn rich distributions over images audio and data which are hard to model with an explicit likelihood - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6953-bayesian-gan

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Efficient Algorithms for Smooth Minimax Optimization

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Kiran K Thekumparampil Prateek Jain Praneeth Netrapalli Sewoong Oh Abstract This paper studies first order methods for solving smooth minimax - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/9430-efficient-algorithms-for-smooth-minimax-optimization

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Adaptive Methods for Nonconvex Optimization NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

In this work we provide a new analysis of such methods applied to nonconvex stochastic optimization problems characterizing the effect of increasing  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8186-adaptive-methods-for-nonconvex-optimization

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Assisted Learning: A Framework for MultiOrganization Learning

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Theoretical and experimental studies including realworld medical benchmarks show that Assisted Learning can often achieve nearoracle learning performance as - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/a7b23e6eefbe6cf04b8e62a6f0915550-Paper.pdf

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Reviews: Twin Auxilary Classifiers GAN

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Though the analysis uses wellknown tools it helps to understand ACGAN in your work you present ACGAN as being a particular instantiation of a cGAN  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2019/file/4ea06fbc83cdd0a06020c35d50e1e89a-Reviews.html

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Reviews: Supervised Word Movers Distance

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

This paper proposes a supervised metric learning approach built on top of the recent “wordmovers distance” [19] (a transport distance applied to word2vec  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2016/file/10c66082c124f8afe3df4886f5e516e0-Reviews.html

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Efficient inference for timevarying behavior during learning

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Nicholas A Roy Ji Hyun Bak Athena Akrami Carlos Brody Jonathan W Pillow Abstract The process of learning new behaviors over time is a  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/7812-efficient-inference-for-time-varying-behavior-during-learning

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Supplementary Materials of AutoPanoptic NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Supplementary Materials of AutoPanoptic: for Panoptic Segmentation heuristic method similar to PanopticFPN [2] to derive the panoptic outputs - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/ec1f764517b7ffb52057af6df18142b7-Supplemental.pdf

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Deep Archimedean Copulas NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

In this paper we introduce ACNet a novel differentiable neural network architecture that enforces structural properties and enables one to learn an  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/hash/10eb6500bd1e4a3704818012a1593cc3-Abstract.html

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Poincaré Embeddings for Learning NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

In this work we introduce a new approach for learning hierarchical representations of symbolic data by embedding them into hyperbolic space or more  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/7213-poincare-embeddings-for-learning-hierarchical-representations

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a Semiparametric Framework for Linear Dimension Reduction

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

We propose a new linear method for dimension reduction to identify nonGaussian components in high dimensional data Our method NGCA (nonGaussian component  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2854-non-gaussian-component-analysis-a-semi-parametric-framework-for-linear-dimension-reduction

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Bootstrap Your Own Latent A New Approach to Self

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

consider the following objective that extends the InfoNCE objective [10 84] (see Appendix G4) 8 Page 9 InfoNCEαβ - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/f3ada80d5c4ee70142b17b8192b2958e-Paper.pdf

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Neural Tangent Kernel: Convergence NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Arthur Jacot Franck Gabriel Clement Hongler Abstract At initialization artificial neural networks (ANNs) are equivalent to Gaussian processes  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8076-neural-tangent-kernel-convergence-and-generalization-in-neural-networks

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Hyperbolic Graph Convolutional Neural Networks NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Graph convolutional neural networks (GCNs) embed nodes in a graph into Euclidean space which has been shown to incur a large distortion when embedding  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8733-hyperbolic-graph-convolutional-neural-networks

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Nonconvex LowRank Tensor Completion from Noisy Data

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

We study a completion problem of broad practical interest: the reconstruction of a lowrank symmetric tensor from highly incomplete and randomly corrupted  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8462-nonconvex-low-rank-tensor-completion-from-noisy-data

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Robust MultiAgent Reinforcement Learning with Model

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Summary and Contributions: The paper extends the robust MDP framework to robust Markov games in the multiagent case The paper proposes Qlearning and  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/774412967f19ea61d448977ad9749078-Review.html

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Deep Poisson Factor Modeling NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Ricardo Henao Zhe Gan James Lu Lawrence Carin Abstract We propose a new deep architecture for topic modeling based on Poisson Factor Analysis  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/5786-deep-poisson-factor-modeling

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Copeland Dueling Bandits NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Masrour Zoghi Zohar S Karnin Shimon Whiteson Maarten de Rijke Abstract A version of the dueling bandit problem is addressed in which a  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6023-copeland-dueling-bandits

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Variational Policy Search via Trajectory Optimization

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

We present a method that uses trajectory optimization as a powerful exploration strategy that guides the policy search A variational decomposition of a maximum  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/5178-variational-policy-search-via-trajectory-optimization

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Crosschannel Communication Networks NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Jianwei Yang Zhile Ren Chuang Gan Hongyuan Zhu Devi Parikh Abstract Convolutional neural networks process input data by sending channelwise  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8411-cross-channel-communication-networks

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Export Reviews Discussions Author Feedback and Meta

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Paper on learning CNNbased semantic image segmentation models from a large number of "Learning Hierarchical Features for Scene Labeling" TPAMI 2013 - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2015/file/f47d0ad31c4c49061b9e505593e3db98-Reviews.html

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CrossView Consistency in 3D Object Detection with Hybrid

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Qi Chen ∗ learning directly from 3D LiDAR point clouds has become increasingly The LiDAR point clouds consists of N points and each point is  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/f2fc990265c712c49d51a18a32b39f0c-Paper.pdf

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Export Reviews Discussions Author Feedback and Meta

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

why not reporting SPDCroh1 together with the other methods the serial by demonstrating the performance of the algorithm in the distributed setting  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2015/file/01f78be6f7cad02658508fe4616098a9-Reviews.html

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Differentially Private ChangePoint Detection NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Rachel Cummings Sara Krehbiel Yajun Mei Rui Tuo Wanrong Zhang Abstract The changepoint detection problem seeks to identify distributional  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8280-differentially-private-change-point-detection

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A Better Way to Pretrain Deep Boltzmann Machines NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Geoffrey E Hinton Russ R Salakhutdinov Abstract We describe how the pretraining algorithm for Deep Boltzmann Machines (DBMs) is related to  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/4610-a-better-way-to-pretrain-deep-boltzmann-machines

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Attend Infer Repeat: Fast Scene Understanding with

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

We present a framework for efficient inference in structured image models that explicitly reason about objects We achieve this by performing probabilistic  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6230-attend-infer-repeat-fast-scene-understanding-with-generative-models

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Stochastic Optimization for Largescale Optimal Transport

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

We propose a new class of stochastic optimization algorithms to cope with largescale problems routinely encountered in machine learning applications - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6566-stochastic-optimization-for-large-scale-optimal-transport

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Neural Machine Translation with Soft Prototype NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Neural machine translation models usually use the encoderdecoder prototype generation most previous approaches use a single sequence as a hard  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8861-neural-machine-translation-with-soft-prototype.pdf

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Controllable Unsupervised Text Attribute Transfer via Editing

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

attribute (eg positive sentiment) the goal of the task is to generate a new text with a different Generating sentences from a continuous space - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/9284-controllable-unsupervised-text-attribute-transfer-via-editing-entangled-latent-representation.pdf

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Enhancing the Locality and Breaking the Memory Bottleneck

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting Part of Advances in Neural Information Processing  - Information from papers.nips.cc

Information accuracy 100%
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Discriminative Unsupervised Feature NeurIPS Proceedings

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Authors Alexey Dosovitskiy Jost Tobias Springenberg Martin Riedmiller Thomas Brox Abstract Current methods for training convolutional neural networks  - Information from papers.nips.cc

Information accuracy 100%
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Unsupervised Learning of Dense Visual Representations

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

[73] Zhirong Wu Yuanjun Xiong Stella Yu and Dahua Lin Unsupervised feature learning via nonparametric instance discrimination In CVPR 2018 - Information from papers.nips.cc

Information accuracy 100%
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Markov Random Fields for Collaborative Filtering NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

to a user in a collaborativefiltering problem via a Gaussian Markov Random Field (MRF) We build upon Besags autonormal parameterization and pseudo - Information from papers.nips.cc

Information accuracy 100%
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Steering Distortions to Preserve Classes and Neighbors in

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Nonlinear dimensionality reduction of highdimensional data is challenging as the Neighbourhood Component Analysis (NCA) [29] and its neuralnetwork - Information from papers.nips.cc

Information accuracy 100%
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Adaptive Discretization for ModelBased Reinforcement

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

based episodic reinforcement learning algorithm in large (potentially an adaptive partition of the space modelbased and modelfree algorithms perform  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/285baacbdf8fda1de94b19282acd23e2-Paper.pdf

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Characterlevel Convolutional Networks for Text Classification

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Characterlevel Convolutional Networks for Text Classification and deep learning models such as wordbased ConvNets and recurrent neural networks - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/5782-character-level-convolutional-networks-for-text-classification

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Improving BERT with Spanbased Dynamic Convolution

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Convolutional neural networks for sentence classification In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing  - Information from papers.nips.cc

Information accuracy 100%
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How Does Batch Normalization Help Optimization? NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Shibani Santurkar Dimitris Tsipras Andrew Ilyas Aleksander Madry Abstract Batch Normalization (BatchNorm) is a widely adopted technique that  - Information from papers.nips.cc

Information accuracy 100%
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Multiview Contrastive Graph Clustering NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Recently based on GCN One2Multi graph autoencoder clustering (O2MA) framework variational GAE (VGAE) [Kipf and Welling 2016] marginalized GAE (MGAE)  - Information from papers.nips.cc

Information accuracy 100%
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Steering Distortions to Preserve Classes and Neighbors in

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Nonlinear dimensionality reduction of highdimensional data is challenging as 34th Conference on Neural Information Processing Systems (NeurIPS 2020)  - Information from papers.nips.cc

Information accuracy 100%
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SEXNET: A Neural Network Identifies Sex From Human Faces

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

A neural network was trained to discriminate sex in human faces and performed as well as humans on a set of 90 exemplars Images sampled at 30x30 were  - Information from papers.nips.cc

Information accuracy 100%
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Reviews: Guided Policy Search via Approximate Mirror Descent

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Also the results in appendix C on the relationship between KL divergence and total variation are straightforward (see Section 3 of Schulmans TRPO paper:  - Information from papers.nips.cc

Information accuracy 100%
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Active Matting NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Image matting is an illposed problem It requires a user input trimap or some strokes to obtain an alpha matte of the foreground object - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/7710-active-matting

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Joint Tracking of Pose Expression and Texture using

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

We present a generative model and stochastic filtering algorithm for si multaneous tracking of 3D position and orientation nonrigid motion object texture  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2732-joint-tracking-of-pose-expression-and-texture-using-conditionally-gaussian-filters

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Crosslingual Language Model Pretraining NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Recent studies have demonstrated the efficiency of generative pretraining for English natural language understanding In this work we extend this approach  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8928-cross-lingual-language-model-pretraining

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Model Complexity Goodness of Fit NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

We consider modeling the data set D using models indexed by a complexity index k 1 ::: k ::: kmax • For example the models could be finite mixture  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/1865-model-complexity-goodness-of-fit-and-diminishing-returns

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First we would like to thank the reviewers for their thoughtful

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

While [R3] found the experiments convincing reviewers also noted that the "Distilling FreeForm Natural Laws from Experimental Data" Science 2009) - Information from papers.nips.cc

Information accuracy 100%
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OneShot Imitation Learning NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Yan Duan Marcin Andrychowicz Bradly Stadie OpenAI Jonathan Ho Jonas Schneider Ilya Sutskever Pieter Abbeel Wojciech Zaremba  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6709-one-shot-imitation-learning

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Bayesian GAN NeurIPS Proceedings

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Bibtex Metadata Paper Reviews Supplemental benchmarks including SVHN CelebA and CIFAR10 outperforming DCGAN Wasserstein GANs and DCGAN ensembles - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6953-bayesian-gan

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Kernel Measures of Conditional Dependence NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Kenji Fukumizu Arthur Gretton Xiaohai Sun Bernhard Schölkopf Abstract We propose a new measure of conditional dependence of random variables  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/3340-kernel-measures-of-conditional-dependence

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Random Projections for Manifold Learning NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Random Projections for Manifold Learning We propose a novel method for {\em linear} dimensionality reduction of manifold modeled data - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/3191-random-projections-for-manifold-learning

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Reviews: A Simple Practical Accelerated Method for Finite Sums

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

"Linear coupling: An ultimate unification of gradient and mirror descent" where the acceleration results from a primaldual point of view on the progress  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: http://papers.nips.cc/paper/2016/file/4f6ffe13a5d75b2d6a3923922b3922e5-Reviews.html

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Dynamic Network Surgery for Efficient DNNs NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Yiwen Guo Anbang Yao Yurong Chen Abstract Deep learning has become a ubiquitous technology to improve machine intelligence - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6165-dynamic-network-surgery-for-efficient-dnns

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SelfSupervised Graph Transformer on LargeScale Molecular

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

graphs and employ Graph Neural Networks (GNNs) for molecular representation Different from other domains (such as image classification) that have - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/94aef38441efa3380a3bed3faf1f9d5d-Paper.pdf

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A Dual Framework for Lowrank Tensor Completion NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Madhav Nimishakavi Pratik Kumar Jawanpuria Bamdev Mishra Abstract One of the popular approaches for lowrank tensor completion is to use the  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/7793-a-dual-framework-for-low-rank-tensor-completion

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Book NeurIPS Proceedings

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Advances in Neural Information Processing Systems 33 (NeurIPS 2020) Domain Generalization for Medical Imaging Classification with LinearDependency  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020

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Learning Regularization and IllPosed NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Nev ertheless by now there was no formal evidence neither that learning from examples could be seen as an inverse problem nor that theoretical results in  - Information from papers.nips.cc

Information accuracy 100%
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Reviews: OneShot Imitation Learning

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

This paper presents an architecture inspired by recent work in meta learning which generalizes manipulation of a robot arm from a single task demonstration  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2017/file/ba3866600c3540f67c1e9575e213be0a-Reviews.html

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Do Deep Nets Really Need to be Deep? NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Currently deep neural networks are the state of the art on problems such as speech recognition and computer vision In this paper we empirically  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/5484-do-deep-nets-really-need-to-be-deep

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Book NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Advances in Neural Information Processing Systems 33 (NeurIPS 2020) Modeling Task Effects on Meaning Representation in the Brain via ZeroShot MEG  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020

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Teaching a GAN What Not to Learn NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

it must learn to model but also present it with socalled negative Rumi approach results in substantially lower FID scores than the standard GAN - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/29405e2a4c22866a205f557559c7fa4b-Paper.pdf

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Contrastive Learning of GlobalLocal Video Representations

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Learning video representations from the natural audio visual correspondence has A simple framework for contrastive learning of visual representations - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2021/file/38ef4b66cb25e92abe4d594acb841471-Paper.pdf

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Adaptive Discretization for ModelBased Reinforcement

papers.nips.cc

Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

based episodic reinforcement learning algorithm in large (potentially an adaptive partition of the space modelbased and modelfree algorithms perform  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/285baacbdf8fda1de94b19282acd23e2-Paper.pdf

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Book NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Bayes Factor Computation in Neural Circuits Wenhao Zhang Si Wu Brent Doiron On the Convergence Rate of Training Recurrent Neural Networks Zeyuan  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2019

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Simple and Principled Uncertainty NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

In the rest of this paper we first theoretically motivate the importance of distance awareness for a models ability uncertainty estimation by studying it as a  - Information from papers.nips.cc

Information accuracy 100%
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Statistical Convergence of Kernel CCA NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Kenji Fukumizu Arthur Gretton Francis Bach Abstract While kernel canonical correlation analysis (kernel CCA) has been applied in many problems  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2891-statistical-convergence-of-kernel-cca

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Weakly Supervised Instance Segmentation using the

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

This paper presents a weakly supervised instance segmentation method that consumes training data with tight bounding box annotations The major difficulty lies  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8885-weakly-supervised-instance-segmentation-using-the-bounding-box-tightness-prior

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Learning Regularization and IllPosed NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Learning Regularization and IllPosed Inverse Problems is defined as the solution of the regularized least squares problem 1 min{ (f (xi) yi)2 + f  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2722-learning-regularization-and-ill-posed-inverse-problems

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LogLikelihood Ratio Minimizing Flows: Towards Robust and

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

normalizing flows for maximum likelihood density estimation made great strides in defining new (d) objective value vs quality of alignment in SNGAN - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/f169b1a771215329737c91f70b5bf05c-Paper.pdf

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Unsupervised Learning of Dense Visual Representations

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Deep clustering for unsupervised learning of visual features In ECCV 2018 [4] LiangChieh Chen George Papandreou Iasonas Kokkinos Kevin Murphy and Alan L  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/3000311ca56a1cb93397bc676c0b7fff-Paper.pdf

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Sparse Representation for Gaussian Process Models

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Lehel Csató Manfred Opper Abstract We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/1893-sparse-representation-for-gaussian-process-models

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Simple and Principled Uncertainty NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu∗ uncertainty estimation that require only a single deep neural network (DNN) By - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/543e83748234f7cbab21aa0ade66565f-Paper.pdf

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LowRank Tucker Decomposition of NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Osman Asif Malik Stephen Becker Abstract We propose two randomized algorithms for lowrank Tucker decomposition of tensors - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8213-low-rank-tucker-decomposition-of-large-tensors-using-tensorsketch

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Provably Efficient Qlearning with Function Approximation via

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Our algorithm introduces a new notion the Distribution Shift Error Checking (DSEC) oracle This oracle tests whether there exists a function in the function  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/9018-provably-efficient-q-learning-with-function-approximation-via-distribution-shift-error-checking-oracle

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The Autoencoding Variational Autoencoder NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Does a Variational AutoEncoder (VAE) consistently encode typical samples gener deep bidirectional transformers for language understanding 2018 - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/ac10ff1941c540cd87c107330996f4f6-Paper.pdf

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Stochastic Expectation Propagation NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Expectation propagation (EP) is a deterministic approximation algorithm that is often used to perform approximate Bayesian parameter learning - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/5760-stochastic-expectation-propagation

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Shared Experience ActorCritic for MultiAgent Reinforcement

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

“Agents Teaching Agents: A Survey on Interagent Transfer Learning” In: Autonomous Agents and MultiAgent Systems 341 (2020) [9] Lasse Espeholt Raphaël  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/7967cc8e3ab559e68cc944c44b1cf3e8-Paper.pdf

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Book NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

A graph similarity for deep learning Seongmin Ok Statistical Guarantees of Distributed Nearest Neighbor Classification Jiexin Duan Xingye Qiao  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020

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Pruning Filter in Filter NeurIPS Proceedings

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

1 Introduction Deep Neural Networks (DNNs) have achieved remarkable progress in many areas including speech recognition [1] computer vision [2 3]  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020/file/ccb1d45fb76f7c5a0bf619f979c6cf36-Paper.pdf

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HyperGCN: A New Method For Training Graph Convolutional

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Motivated by the fact that a graph convolutional network (GCN) has been effective for graphbased SSL we propose HyperGCN a novel GCN for SSL on attributed  - Information from papers.nips.cc

Information accuracy 100%
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Private Hypothesis Selection NeurIPS Proceedings

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Authors Mark Bun Gautam Kamath Thomas Steinke Steven Z Wu Abstract We provide a differentially private algorithm for hypothesis selection - Information from papers.nips.cc

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Faster DBSCAN via subsampled similarity queries NeurIPS

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DBSCAN is a popular densitybased clustering algorithm It computes the ϵ neighborhood graph of a dataset and uses the connected components of the high - Information from papers.nips.cc

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OnceforAll Adversarial Training: InSitu Tradeoff between

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trade offs between its standard and robust accuracies achieve insitu tradeoff among accuracy robustness and model complexity altogether  - Information from papers.nips.cc

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Graph Policy Network for Transferable Active Learning on

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Graph neural networks (GNNs) have been attracting increasing popularity due to learning for neural machine translation with reinforcement learning - Information from papers.nips.cc

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Approximating Interactive Human Evaluation with SelfPlay for

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Authors Asma Ghandeharioun Judy Hanwen Shen Natasha Jaques Craig Ferguson Noah Jones Agata Lapedriza Rosalind Picard  - Information from papers.nips.cc

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Switched Latent Force Models for Movement Segmentation

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Latent force models encode the interaction between multiple related dynamical systems in the form of a kernel or covariance function - Information from papers.nips.cc

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SchNet: A continuousfilter convolutional neural network for

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smooth potential energy surface and the resulting forcefield is guaranteed to be energy Generalized neuralnetwork representation of highdimensional - Information from papers.nips.cc

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Learning to Detect Objects with a 1 Megapixel Event Camera

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Event cameras encode visual information with high temporal precision low data rate and highdynamic range Thanks to these characteristics event cameras  - Information from papers.nips.cc

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Learning Structured Output Representation using Deep

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Learning Structured Output Representation using Deep Conditional model is trained efficiently in the framework of stochastic gradient variational Bayes  - Information from papers.nips.cc

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SelfSupervised Graph Transformer on NeurIPS Proceedings

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Recent researches abstract molecules as graphs and employ Graph Neural Networks (GNNs) for molecular representation learning Nevertheless two issues impede  - Information from papers.nips.cc

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Efficient Graph Generation with Graph Recurrent Attention

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Authors Renjie Liao Yujia Li Yang Song Shenlong Wang Will Hamilton David K Duvenaud Raquel Urtasun Richard Zemel  - Information from papers.nips.cc

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FLEX: Unifying Evaluation for FewShot NLP NeurIPS

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2Benchmark leaderboard and benchmark creation toolkit: https://githubcom/allenai/flex BoolQ: Exploring the Surprising Difficulty of Natural Yes/No - Information from papers.nips.cc

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RANet: Region Attention Network for Semantic Segmentation

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Dual attention network for scene segmentation arXiv preprint arXiv:180902983 2018 10 Page 11 [17]  - Information from papers.nips.cc

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Mutual information for symmetric rankone matrix estimation

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Mutual information for symmetric rankone matrix estimation: A proof of the Factorizing lowrank matrices has many applications in machine learning and  - Information from papers.nips.cc

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ImageNet Classification with Deep NeurIPS Proceedings

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We trained a large deep convolutional neural network to classify the 13 million highresolution images in the LSVRC2010 ImageNet training set into the 1000  - Information from papers.nips.cc

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Cooled and Relaxed Survey Propagation for MRFs NeurIPS

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Authors Hai Chieu Wee Lee Yee Teh Abstract We describe a new algorithm Relaxed Survey Propagation (RSP) for finding MAP configurations in Markov  - Information from papers.nips.cc

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Variational Laws of Visual Attention for NeurIPS Proceedings

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Authors Dario Zanca Marco Gori Abstract Computational models of visual attention are at the crossroad of disciplines like cognitive science  - Information from papers.nips.cc

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Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6972-variational-laws-of-visual-attention-for-dynamic-scenes

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ImageNet Classification with Deep NeurIPS Proceedings

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Authors Alex Krizhevsky Ilya Sutskever Geoffrey E Hinton Abstract We trained a large deep convolutional neural network to classify the 13 million  - Information from papers.nips.cc

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Adversarial TeacherStudent Representation Learning for

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yet effective approach of Adversarial TeacherStudent Representation Learning with the goal of deriving the domain generalizable representations via  - Information from papers.nips.cc

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Simple and Principled Uncertainty Estimation with

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Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu∗ uncertainty estimation that require only a single deep neural network (DNN) By - Information from papers.nips.cc

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Scene Segmentation with CRFs Learned from Partially

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Conditional Random Fields (CRFs) are an effective tool for a variety of different data segmentation and labeling tasks including visual scene interpretation  - Information from papers.nips.cc

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Book NeurIPS Proceedings

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A Causal View on Robustness of Neural Networks Cheng Zhang Kun Zhang Joseph Tighe Improving Inference for Neural Image Compression Yibo Yang  - Information from papers.nips.cc

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Book NeurIPS Proceedings

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Visual Sequence Learning in Hierarchical Prediction Networks and Primate and Flexible MultiTask Classification using Conditional Neural Adaptive - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2019

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Unsupervised Learning of Dense Visual Representations

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unsupervised visual representation learning momentum contrast mechanism [26] to efficiently use a large number of negative samples during training - Information from papers.nips.cc

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Reviews: Improving Variational Autoencoders with Inverse

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The authors also introduce a ResNetbased deep convolutional VAE architecture The authors propose an extension of normalizing flows for improving the  - Information from papers.nips.cc

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MeshTensorFlow: Deep Learning for Supercomputers

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Unfortunately efficient modelparallel algorithms tend to be complicated to Using TPU meshes of up to 512 cores we train Transformer models with up to  - Information from papers.nips.cc

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Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/8242-mesh-tensorflow-deep-learning-for-supercomputers

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Tight convex relaxations for sparse NeurIPS Proceedings

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Based on a new atomic norm we propose a new convex formulation for sparse matrix factorization problems in which the number of nonzero elements of the  - Information from papers.nips.cc

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Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/5408-tight-convex-relaxations-for-sparse-matrix-factorization

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Learning to Reconstruct Shapes from Unseen Classes

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

From a single image humans are able to perceive the full 3D shape of an object by exploiting learned shape priors from everyday life Contemporary single  - Information from papers.nips.cc

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Algorithms for HyperParameter Optimization NeurIPS

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Traditionally hyperparameter optimization has been the job of humans because they can be very efficient in regimes where only a few trials are possible - Information from papers.nips.cc

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Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/4443-algorithms-for-hyper-parameter-optimization

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Book NeurIPS Proceedings

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A graph similarity for deep learning Seongmin Ok CrossScale Internal Graph Neural Network for Image SuperResolution Shangchen Zhou Jiawei Zhang  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2020

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On the Fairness of Disentangled Representations NeurIPS

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Recently there has been a significant interest in learning disentangled representations as they promise increased interpretability generalization to  - Information from papers.nips.cc

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Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/9603-on-the-fairness-of-disentangled-representations

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Discriminative Unsupervised Feature NeurIPS Proceedings

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In this paper we present an approach for training a convolutional neural network using only unlabeled data We train the network to discriminate between a set  - Information from papers.nips.cc

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Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/5548-discriminative-unsupervised-feature-learning-with-convolutional-neural-networks

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CAMGAN: Continual Adaptation Modules for Generative

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a continual learning approach for generative adversarial networks (GANs) by designing and leveraging parameterefficient feature map transformations - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2021/hash/8073bd4ed0fe0c330290c58056a2cd5e-Abstract.html

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RFCN: Object Detection via Regionbased Fully

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Jifeng Dai Yi Li Kaiming He Jian Sun Abstract We present regionbased fully convolutional networks for accurate and efficient object  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/6465-r-fcn-object-detection-via-region-based-fully-convolutional-networks

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Learning with Local and Global Consistency NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Dengyong Zhou Olivier Bousquet Thomas Lal Jason Weston Bernhard Schölkopf Abstract We consider the general problem of learning from labeled  - Information from papers.nips.cc

Information accuracy 100%
Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/2506-learning-with-local-and-global-consistency

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HighThroughput Synchronous Deep RL

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Throughput Synchronous Deep Reinforcement Learning (HTSRL) performs distributed training at a large scale eg 128 GPUs and achieves impressive  - Information from papers.nips.cc

Information accuracy 100%
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Multimodal FewShot Learning with Frozen Language Models

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fewshot learning ability to a multimodal setting (vision and language) Prefix tuning is a method for prompting a language model to produce output of a  - Information from papers.nips.cc

Information accuracy 100%
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MultiView Learning of Word Embeddings via CCA NeurIPS

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Multi View Learning of Word Embeddings via CCA been substantial interest in using large amounts of unlabeled data to learn word representations which  - Information from papers.nips.cc

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Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/4193-multi-view-learning-of-word-embeddings-via-cca

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Deep NonBlind Deconvolution via Generalized LowRank

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Deep NonBlind Deconvolution via Generalized LowRank Approximation In this paper we present a deep convolutional neural network to capture the  - Information from papers.nips.cc

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Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/7313-deep-non-blind-deconvolution-via-generalized-low-rank-approximation

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Contrastive Learning of GlobalLocal Video Representations

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In each space we define a crossmodal contrastive objective that compare audiovisual signals in the multiple instance learning framework2 - Information from papers.nips.cc

Information accuracy 100%
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The Description Length of Deep Learning models NeurIPS

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Author: openj-gate.com ~ Tags: papers.nips.cc ~ Date: 2022/11/24

Authors Léonard Blier Yann Ollivier Abstract Deep learning models often have more parameters than observations and still perform well - Information from papers.nips.cc

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Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/7490-the-description-length-of-deep-learning-models

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On the consistency theory of high dimensional variable

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The rapidly growing data dimension has brought new challenges to statistical variable selection a crucial technique for identifying important variables to  - Information from papers.nips.cc

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Read more from papers.nips.cc information was found here: https://papers.nips.cc/paper/5933-on-the-consistency-theory-of-high-dimensional-variable-screening.pdf

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