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April 3 21 Finite State Machines 22 Pushdown Automata 23

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A pushdown automaton is a finite state machine with the addition of a stack This provides more com putational power because the stack allows an unlimited - Information from courses.cs.washington.edu

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Fermionic Simulation and Trotterization

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a) JordanWigner transform and relevant circuits b) Error scaling and asymptotic bounds with the LieTrotterSuzuki Formula - Information from courses.cs.washington.edu

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Binary Image Analysis

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▫ Many touch – bad! ▫ Salt and pepper noise from thresholding ▫ How useable is this data? - Information from courses.cs.washington.edu

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CSE599J: Personal Robotics Clinic: Algorithms and Applications

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Personal Robotics Applications "ROBOTS IN THE HOUSE!" Keenan Wyrobek Leila Takayama Graph Algorithms from a section of a textbook - Information from courses.cs.washington.edu

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Exercise 1: Majorization and Random Permutations

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for all i Lets show that this vector is indeed majorized by all other vectors of probability (note that I didnt ask for this but it is nice to prove it) - Information from courses.cs.washington.edu

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Welcome to CSE 163 Winter 2021! University of Washington

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In contrast CSE163 emphasizes the efficient use of those concepts for data programming In this course students will learn: More advanced programming concepts - Information from courses.cs.washington.edu

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Alex Mariakakis From CSE 501…again

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FlowDroid : the first fully context field object and flowsensitive taint analysis which considers the Android application lifecycle and UI widgets - Information from courses.cs.washington.edu

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Tuning Random Forest Hyperparameters across Big Data

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Tuning Random Forest Hyperparameters across Big Data Systems By Ishna Kaul Introduction Motivation The amount of data organizations are generating has - Information from courses.cs.washington.edu

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61 Weighted Interval Scheduling

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Unweighted Interval Scheduling Review Recall Greedy algorithm works if all weights are 1 □ Consider jobs in ascending order of finish time - Information from courses.cs.washington.edu

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A Review of Computer Vision Segmentation Algorithms

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Remote sensing systems work on multispectral images that captures image data at specific frequen cies across the electromagnetic spectrum These images - Information from courses.cs.washington.edu

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CSE 599d Quantum Computing Quantum Entanglement and

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Quantum Entanglement and Bells Theorem Dave Bacon proof for the most general case we considered we might get a little uncomfortable - Information from courses.cs.washington.edu

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CSE 312: Mathematical Typesetting in Word and LaTeX

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It is recommended to use the equation editor (in word and latex) to do any numerics ( Union of many \bigcup_(i1)^n[+space]E_i \bigcup_{i1}^{n}{E_i} - Information from courses.cs.washington.edu

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Introduction to Database Systems CSE 444 Washington

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CSE444 as the first word in the Subject line Otherwise it will be ignored 3 Textbook(s) A First Course in Database Systems - Information from courses.cs.washington.edu

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Team Dynamics CSE 403 Slides

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Communication issues Diffusion of responsibility Working by inertia not planning ahead Conflict or mistrust between team members - Information from courses.cs.washington.edu

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CSE 599 Autumn 2020 Generative Models

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[Stanford CS 236]: Deep Generative Models [Berkeley CS 294158]: Deep Unsupervised Learning Discussion Forum and Email Communication Discussion will take - Information from courses.cs.washington.edu

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CSE 312 Course Info

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Dimitri P Bertsekas and John N Tsitsiklis Introduction to Probability /en/eLearning/MathBertsekas_Tsitsiklis_Introduction_to_probabilitypdf - Information from courses.cs.washington.edu

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UML Sequence Diagrams

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What is a UML sequence diagram? Sequence diagram: an “interaction diagram” that 2nd most used UML diagram (behind class diagram) - Information from courses.cs.washington.edu

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CSE 522: Algorithms and Uncertainty (Spring 2017)

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June 2 Student presentations Linear coupling: An ultimate unification of gradient and mirror descent · Towards minimax policies for online linear - Information from courses.cs.washington.edu

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cse 431: introduction to the theory of computation Fall 2019

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That includes everything except the solutions to current homework The third edition has an extra section 24 on deterministic contextfree languages - Information from courses.cs.washington.edu

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Sample Summary: University of Washington Computer

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Reading Summary Description and Sample Reading Summary article before mistake in writing their summaries that can lead to score deductions: - Information from courses.cs.washington.edu

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Sample Summary: University of Washington Computer

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Reading Summary Description and Sample Reading Summary (be specific! cite specific examples or ideas used in the paper) article before - Information from courses.cs.washington.edu

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Systemonchip design ASIC 2001 Proceedings 4th

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Overview of SystemOnChip Design Chip designs have for the last 20 years reused design processor class and assembly coding is still very much - Information from courses.cs.washington.edu

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cse 431: introduction to the theory of computation Fall 2019

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Use this board to discuss the content of the course That includes everything except the solutions to current homework problems It is also acceptable to ask - Information from courses.cs.washington.edu

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Use of Ontologies in Pervasive Computing Environments

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These standards define the interfaces and formats for descriptions but they leave most of the specific content—the “semantics” of the - Information from courses.cs.washington.edu

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CSE 599d Quantum Computing Quantum Phase Estimation

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necessary to get to the point where we can understand Shors algorithm I QUANTUM PHASE ESTIMATION ALGORITHM Lets look at the quantum Fourier transform - Information from courses.cs.washington.edu

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CSE 312: Mathematical Typesetting in Word and LaTeX

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In Word you will need to press space to see the command converted to the symbol sometimes It is recommended to use the equation editor (in word and latex) to - Information from courses.cs.washington.edu

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Fermionic Simulation and Trotterization

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a) JordanWigner transform and relevant circuits b) Error scaling and asymptotic bounds “Simulating Hamiltonian Dynamics” Microsoft Q# documentation - Information from courses.cs.washington.edu

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Introduction to Database Systems CSE 414 University of

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Textbook Main textbook available at the bookstore: • Database Systems: The Complete Book Hector GarciaMolina Jeffrey Ullman Jennifer Widom - Information from courses.cs.washington.edu

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CSE 312: Foundations of Computing II

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Sheldon Ross A First Course in Probability (10th Ed) Pearson Prentice Hall 2018 • Berkeleys EECS 70 online practice http://practiceeecs70org/#/home - Information from courses.cs.washington.edu

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CSE 322: Introduction to Formal Models in Computer Science

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1/6 1/12: Chapter 1 all sections and Chapter 2 sections 12 Introduction to Automata Theory Languages and Computation Second Edition - Information from courses.cs.washington.edu

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61 Weighted Interval Scheduling

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Unweighted Interval Scheduling Review Recall Greedy algorithm works if all weights are 1 □ Consider jobs in ascending order of finish time - Information from courses.cs.washington.edu

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Chapter 4 41 Interval Scheduling

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c d 4 Interval Scheduling: Greedy Algorithms Greedy template Consider jobs in some order Take each job provided its compatible with the ones already - Information from courses.cs.washington.edu

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cse 431: introduction to the theory of computation Fall 2019

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Textbook: Michael Sipser Introduction to the Theory of Computation Any of the first international second or third editions will work Earlier editions - Information from courses.cs.washington.edu

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Inferring and Reasoning about Shapes in TensorFlow

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TensorFlow shape tensor Python machine learning com To specify an unknown or dynamic dimension in the - Information from courses.cs.washington.edu

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Dijkstras Algorithm

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Dijkstras Algorithm CSE 373 SP 18 KASEY CHAMPION 1 Dijkstra(Graph G Vertex source) Shortest path algorithms are obviously useful for GoogleMaps - Information from courses.cs.washington.edu

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Sample Summary: University of Washington Computer

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Reading Summary Description and Sample Reading Summary article before students electronically because this would imply unsuitable sharing of work - Information from courses.cs.washington.edu

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Using the Gnu Debugger

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GDB is a debugger that will help you to debug programs from various languages C:17 17 for (i0 i < strlen(*string)1 i++) { (gdb) list 12 } 13 14 void - Information from courses.cs.washington.edu

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Expressive Variational Autoencoders

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The Gaussian VAE parameterizes the prior r(z) conditional likelihood p(xz) posterior approximations more expressive makes use of the normalizing flow - Information from courses.cs.washington.edu

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Use of Ontologies in Pervasive Computing Environments

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These standards define the interfaces and formats for descriptions but they leave most of the specific content—the “semantics” of the - Information from courses.cs.washington.edu

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CSEP 573 Final Exam – March 12 2016

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True / False – For answering conditional queries in Bayesian networks Question 3 – Hidden Markov Models: Tricky Coins – 20 points - Information from courses.cs.washington.edu

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CSE 599d Quantum Computing FaultTolerant Quantum

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Fault Tolerant Quantum Computation and the Threshold Theorem Dave Bacon Department of Computer Science & Engineering University of Washington - Information from courses.cs.washington.edu

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Naïve Bayes Classifiers

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Conditional Independence Conditional Independence tells us that: Two events A and B are conditionally independent given C if - Information from courses.cs.washington.edu

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Shared Music

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Shared Music Page 2 Vision ○ An application that allows users to suggest songs to their friends ○ Works as an extension to an existing music - Information from courses.cs.washington.edu

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CSE 544 Syllabus

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Database Management Systems 3rd Edition Foundations of Databases (Abiteboul Hull & Vianu) Database Systems: the complete book (Ullman - Information from courses.cs.washington.edu

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CSE341 Lecture Notes 17: Smalltalk and OOP library design

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Data abstraction Abstract data types An abstract data type is a programmerdefined type whose internal representation is hidden and which can only be - Information from courses.cs.washington.edu

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EDUCATION April 3 21 Finite State Machines 22 Pushdown Automata 23

EDUCATION Fermionic Simulation and Trotterization

EDUCATION Binary Image Analysis

EDUCATION CSE599J: Personal Robotics Clinic: Algorithms and Applications

EDUCATION Exercise 1: Majorization and Random Permutations

EDUCATION Welcome to CSE 163 Winter 2021! University of Washington

EDUCATION Alex Mariakakis From CSE 501…again

EDUCATION Tuning Random Forest Hyperparameters across Big Data

EDUCATION 61 Weighted Interval Scheduling

EDUCATION A Review of Computer Vision Segmentation Algorithms

EDUCATION CSE 599d Quantum Computing Quantum Entanglement and

EDUCATION CSE 312: Mathematical Typesetting in Word and LaTeX

EDUCATION Introduction to Database Systems CSE 444 Washington

EDUCATION Team Dynamics CSE 403 Slides

EDUCATION CSE 599 Autumn 2020 Generative Models

EDUCATION CSE 312 Course Info

EDUCATION UML Sequence Diagrams

EDUCATION CSE 522: Algorithms and Uncertainty (Spring 2017)

EDUCATION cse 431: introduction to the theory of computation Fall 2019

EDUCATION Sample Summary: University of Washington Computer

EDUCATION Sample Summary: University of Washington Computer

EDUCATION Systemonchip design ASIC 2001 Proceedings 4th

EDUCATION cse 431: introduction to the theory of computation Fall 2019

EDUCATION Use of Ontologies in Pervasive Computing Environments

EDUCATION CSE 599d Quantum Computing Quantum Phase Estimation

EDUCATION CSE 312: Mathematical Typesetting in Word and LaTeX

EDUCATION Fermionic Simulation and Trotterization

EDUCATION Introduction to Database Systems CSE 414 University of

EDUCATION CSE 312: Foundations of Computing II

EDUCATION CSE 322: Introduction to Formal Models in Computer Science

EDUCATION 61 Weighted Interval Scheduling

EDUCATION Chapter 4 41 Interval Scheduling

EDUCATION cse 431: introduction to the theory of computation Fall 2019

EDUCATION Inferring and Reasoning about Shapes in TensorFlow

EDUCATION Dijkstras Algorithm

EDUCATION Sample Summary: University of Washington Computer

EDUCATION Using the Gnu Debugger

EDUCATION Expressive Variational Autoencoders

EDUCATION Use of Ontologies in Pervasive Computing Environments

EDUCATION CSEP 573 Final Exam – March 12 2016

EDUCATION CSE 599d Quantum Computing FaultTolerant Quantum

EDUCATION Naïve Bayes Classifiers

EDUCATION Shared Music

EDUCATION CSE 544 Syllabus

EDUCATION CSE341 Lecture Notes 17: Smalltalk and OOP library design

Trending Searches

April 3 21 Finite State Machines 22 Pushdown Automata 23

Fermionic Simulation and Trotterization

Binary Image Analysis

CSE599J: Personal Robotics Clinic: Algorithms and Applications

Exercise 1: Majorization and Random Permutations

Welcome to CSE 163 Winter 2021! University of Washington

Alex Mariakakis From CSE 501…again

Tuning Random Forest Hyperparameters across Big Data

61 Weighted Interval Scheduling

A Review of Computer Vision Segmentation Algorithms

CSE 599d Quantum Computing Quantum Entanglement and

CSE 312: Mathematical Typesetting in Word and LaTeX

Introduction to Database Systems CSE 444 Washington

Team Dynamics CSE 403 Slides

CSE 599 Autumn 2020 Generative Models

CSE 312 Course Info

UML Sequence Diagrams

CSE 522: Algorithms and Uncertainty (Spring 2017)

cse 431: introduction to the theory of computation Fall 2019

Sample Summary: University of Washington Computer

Sample Summary: University of Washington Computer

Systemonchip design ASIC 2001 Proceedings 4th

cse 431: introduction to the theory of computation Fall 2019

Use of Ontologies in Pervasive Computing Environments

CSE 599d Quantum Computing Quantum Phase Estimation

CSE 312: Mathematical Typesetting in Word and LaTeX

Fermionic Simulation and Trotterization

Introduction to Database Systems CSE 414 University of

CSE 312: Foundations of Computing II

CSE 322: Introduction to Formal Models in Computer Science

61 Weighted Interval Scheduling

Chapter 4 41 Interval Scheduling

cse 431: introduction to the theory of computation Fall 2019

Inferring and Reasoning about Shapes in TensorFlow

Dijkstras Algorithm

Sample Summary: University of Washington Computer

Using the Gnu Debugger

Expressive Variational Autoencoders

Use of Ontologies in Pervasive Computing Environments

CSEP 573 Final Exam – March 12 2016

CSE 599d Quantum Computing FaultTolerant Quantum

Naïve Bayes Classifiers

Shared Music

CSE 544 Syllabus

CSE341 Lecture Notes 17: Smalltalk and OOP library design