Computer Science
7,622 items in 38 lists
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CS Theory Events Aggregator cstheory-events.org
An aggregator for CS theory workshops and schools.
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Agrawal & Jaiswal. When Machine Learning Meets AI and Game Theory cs229.stanford.edu
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Aspnes. Notes on Randomized Algorithms cs.yale.edu
Supplemental notes to the standard books by Mitzenmacher & Upfals, and Motwani & Raghavan.
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Aspnes. Notes on Discrete Mathematics cs.yale.edu
Fall 2017 of the Yale course CPSC 202a, Mathematical Tools for Computer Science.
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Watrous. Introduction to The Theory of Computing cs.uwaterloo.ca
undergrad introduction to theory of computation
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First cs.ubc.ca
and Second Course in Randomized Algorithms. Columbia. - Respectively, undergrad and grad courses for probabilistic methods in algorithms.
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Rubinstein & Weinberg. Research Masters in TCS cs.princeton.edu
A list of master programs in TCS.
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Livni. COS 511 Theoretical Machine Learning. Princeton cs.princeton.edu
Formally define and study various models that have been proposed for learning. The course will present and contrast the statistical, computational and online models for learning. We will present and rigorously analyze some of the most successful algorithms in machine learning…
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Arora. Overcoming Intractability in Machine Learning cs.princeton.edu
A seminar course that will focus on the following phenomenon: many problems in machine learning are formally intractable (e.g., NP-hard). Nevertheless they are solved in practice by heuristics. Can we design algorithms with provable guarantees (running time, solution quality)?
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Arora. The Computational Universe cs.princeton.edu
Takes us on a broad sweep of scientific knowledge and related technologies: propositional logic of the ancient Greeks (microprocessors); quantum mechanics (silicon chips); network and system phenomena (internet and search engines); computational intractability (secure…
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Arora. Advanced Algorithm Design cs.princeton.edu
Notably uses ideas such as randomness, approximation, high dimensional geometry. Faces uncertainty, approaches to handle big data, handling intractability, heuristic approaches, ..etc.
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Arora. Thinking Like a Theorist. Princeton cs.princeton.edu
It covers a large number of the math/CS topics that you need to know for reading and doing research in Computer Science Theory.
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Arora. A Theorist's Toolkit. Princeton cs.princeton.edu
Aimed primarily at first and second year graduate students who plan to do research in theoretical computer science. We will introduce probabilistic, algebraic, combinatorial, and algorithmic methods useful in proofs.
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Koutsoupias. Probability and Computing. Oxford cs.ox.ac.uk
Introduction to probabilistic methods in computer science.
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Robert Robere. Proof Complexity: Algorithms and Lower Bounds cs.mcgill.ca
An introduction to modern proof complexity, emphasizing its connections with computational complexity and algorithms in optimization.
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Dinitz. Approximation Algorithms. Johns Hopkins cs.jhu.edu
It includes greedy, local search, dynamic programming, randomized rounding, tree embeddings, and semidefinite programming.
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Eva Tardos. Algorithmic Game Theory cs.cornell.edu
It combines algorithmic thinking with game-theoretic, or, more generally, economic concepts. The course will study a range of topics at this interface. The only prerequisite to the course is mathematical thinking.
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Cornell. Functional Programming in Ocaml cs.cornell.edu
A modern course on data structures and functional programming using OCaml.
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Halpern. CS 2802: Discrete Structures - Honors. 2020. Cornell cs.cornell.edu
Honors lecture notes on discrete math - Homework
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O'Donnell. A Theorist's Toolkit. CMU cs.cmu.edu
It covers a large number of the math/CS topics that you need to know for reading and doing research in Computer Science Theory.
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Blum. You and Your Research: An Advice to a Beginning Graduate Student cs.cmu.edu
Manuel Blum, A very popular figure in TCS, gives research advices for juniors.
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Blum. Intro Machine Learning Theory cs.cmu.edu
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Gupta & Ravi. Approximation Algorithms. CMU cs.cmu.edu
It includes convex programming-based, randomness, and metric methods.
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Brown. Resources list for game theory cs.brown.edu
TAs based these notes in large part on the lecture notes and accompanying videos of Tim Roughgarden's CS 364A and CS 364B courses at Stanford, and Jason Hartline's Mechanism Design and Approximation textbook.
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Mark Bun. CS591 Communication Complexity cs-people.bu.edu
A graduate course which introduces the fundamental results and techniques in the area and some research frontier questions. Themes include: Communication models and the communication complexity zoo, Information vs. communication, Query-to-communication lifting, and Applications
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Chekuri. Approximation Algorithmis Illinois courses.engr.illinois.edu
A broad introduction to results and techniques with an emphasis on fundamental problems and widely applicable tools. Also more advanced and specialized topics.
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Introduction to Discrete Mathematics for Computer Science. UC San-Diego coursera.org
Learn the language of Computer Science. Learn the math that defines computer science, and practice applying it through mathematical proofs and Python code.
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TCS Cheat Sheet cosy.sbg.ac.at
A sheet of notes containing essential toolboxes needed by any theoretical computer scientist.
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Complexity Zoo complexityzoo.net
a wiki of complexity classes.
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Cambridge Foundations of CS cl.cam.ac.uk
It teaches programming and presents some fundamental principles of computer science, especially algorithm design.
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Chekuri. Topics in Algorithms: Algorithmic Game Theory chekuri.cs.illinois.edu
A broad graduate-level introduction to: auctions, existence and computation of equilibria in games and markets, algorithmic mechanism design, price of anarchy and price of stability, games relevant to networks and e-commerce. The emphasis will be on conceptual ideas and…
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Petzold. The Annotated Turing: A Guided Tour Through Alan Turing's Historic Paper on Computability and the Turing… charlespetzold.com
A Guided Tour through Alan Turing's Historic Paper on Computability and the Turing Machine.
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Sipser. Introduction to Theory of Computation cengage.com
A standard text for introducing theory of computation for undergrads.
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Apt & Grädel. Lectures in Game Theory for Computer Scientists cambridge.org
Games provide mathematical models for interaction, and numerous tasks in computer science can be formulated in game-theoretic terms.
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Cutland. Computability: An Introduction to Recursive Function Theory cambridge.org
Intuitively, It explains the idea of a computable function: a function whose values can be calculated in an effective or automatic way.
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Shalev-Shwartz. Understanding Machine Learning: From Theory to Algorithms cambridge.org
It provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms.
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Rao & Yehudayoff. Communication Complexity and Applications cambridge.org
An excellent and very readable introductory textbook to the field of communication complexity.
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Eva Tardos & et.al. Algorithmic Game Theory cambridge.org
Basic chapters on algorithmic methods for equilibria, mechanism design and combinatorial auctions are followed by chapters on important game theory applications such as incentives and pricing, cost sharing, information markets and cryptography and security.
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Tu Delft. Delftse Foundations of Computation books.open.tudelft.nl
A textbook for a one quarter introductory course in theoretical computer science including logic, proof techniques, and set theory. It assumes no prerequisite other than basic programming.
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Barak. Non-technical or Less-technical Writings and Talks boazbarak.org
Posts oriented more for a less-technically matured audience.
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Princeton's Companion. Advice to a Young Mathematician assets.press.princeton.edu
Five contributors draw on their experiences of mathematical life and research, and to offer advice that they might have liked to receive when they were just setting-out on their careers.
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Aaronson. Quantum Computing Since Democritus assets.cambridge.org
It covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory,computability and complexity theory, quantum computing, cryptography, the information content of quantum states, and the interpretation of quantum mechanics.
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here arxiv.org
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Tim Roughgarden. Complexity Theory, Game Theory, and Economics: The Barbados Lectures arxiv.org
A mini-course notes of two-fold goals: mini-course is twofold: (i) Explain how complexity theory has helped illuminate several barriers in economics and game theory; and (ii) Illustrate how game-theoretic questions have led to new and interesting complexity theory, including…
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Odifreddi. Classical Recursion Theory: The Theory of Functions and Sets of Natural Numbers archive.org
An impressive presentation of classical recursion theory. It is highly recommended to everyone interested in recursion theory.
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Rudich & Wigderson. Computational Complexity Theory ams.org
Three weeks of lectures from the IAS/Park City Mathematics Institute Summer School on computational complexity. Topics include reductions, lower-bounds, average-case complexity, randomness, interactive proof systems, probabilistically checkable proofs, quantum computing, and…
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Davis. Computability and Unsolvability amazon.com
In this classic text, Dr. Davis provides a clear introduction to computability, at an advanced undergraduate level, that serves the needs of specialists and non-specialists alike.
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Algorithms with Predictions algorithms-with-predictions.github.io
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