Computer Science
7,622 items in 38 lists
-
Ausiello. The Making of a New Science: A Personal Journey Through the Early Years of Theoretical Computer Science link.springer.com
A story about people, pioneers with diverse backgrounds and characters who established a new field.
-
Lindell. Tutorials on the Foundations of Cryptography link.springer.com
Advanced tutorials appropriate for self-study by experienced researchers,
-
Sommaruga & Strahm. Turing’s Revolution: The Impact of His Ideas about Computability link.springer.com
A collection of historical, technical and philosophical papers.
-
Lacona. LOGIC: Lecture Notes for Philosophy, Mathematics, and Computer Science link.springer.com
Suitable for undergraduate introductions to logic and early graduate courses on logic.
-
Susskind. Three Lectures on Complexity and Black Holes link.springer.com
Important connections between thermodynamics and complexity are proposed and discussed. Pedagogically written, serves as a fundamental introduction to black holes and their complex physical interpretation
-
Lean Proof Assistant lean-lang.org
Lean Proof Assistant.
-
Philip Davis. Toward a Philosophy of Computation jstor.org
Philosophical implication of mathematization and computerization of the world.
-
Vaughan. CS260: Machine Learning Theory jennwv.com
A broad overview of the theoretical foundations underlying common machine learning algorithms.
-
Barak. Introduction to TCS introtcs.org
A modern, brief, and accessible text which introduces theoretical computer science for undergrads. It includes topics not usually included in standard undergrad text-books.
-
Igor Pak. How to Start a Paper igorpak.wordpress.com
Why should you introduce a conceptual preliminary motivating the story of your paper.
-
Aho & Ullman. Foundations of Computer Science i.stanford.edu
A classic math-oriented introduction to computer science.
-
The Univalent Foundations Program Institute for Advanced Study. Homotopy Type Theory: Univalent Foundations of… homotopytypetheory.org
The present book is intended as a first systematic exposition of the basics of univalent foundations, and a collection of examples of this new style of reasoning — but without requiring the reader to know or learn any formal logic, or to use any computer proof assistant.
-
Lee. Randomized Algorithms and Probabilistic Analysis. Washington. homes.cs.washington.edu
Topics include Discrete probability, High-dimensional geometry and statistics, Information and entropy, and Markov chains and convergence to equilibrium.
-
Madhur Tulsiani. Mathematical Toolkit home.ttic.edu
Things prof. Madhur wish he knew in first year of grad school.
-
Blum. An Introduction to the Theory of Machine Learning. TTIC home.ttic.edu
The basic theory underlying machine learning and the process of generalizing from data.
-
Henry Yuen. The Complexity of Entanglement. Fall 2020 henryyuen.net
Focuses on cutting edge topics in quantum information that relate to Complexity of Entanglement. - see this class also
-
Demaine, Gasarch & Hajiaghayi. Computers and Intractability: A Guide to Algorithmic Lower Bounds hardness.mit.edu
A sequel to Garey and Johnson's Computers and Intractability: A Guide to NP-Completeness. New topics include Parameterized Complexity, Lower bounds on approximation, Other hardness assumptions (ETH, 3SUM-conjecture, APSP-conjecture, UGC, Others), Online Algorithms, Streaming…
-
Xu. Topics in Learning and Game Theory haifeng-xu.com
A graduate level course covering topics at the interface between machine learning and game theory.
-
Yaroslavtsev. Hires spreadsheet 2022 grigory.us
A crowdsourced spreadsheet created to collect information about theory hires in year 2022.
-
Fortnow. The Golden Ticket: P, NP, and the Search for the Impossible goldenticket.fortnow.com
A nontechnical introduction to P-NP, its rich history, and its algorithmic implications for everything we do with computers and beyond.
-
Fang. Advanced Topics in Machine Learning and Game Theory feifang.info
A graduate-level course covering the topics at the intersection of machine learning and game theory.
-
Knuth. The Art of Computer Programming en.wikipedia.org
A legendary series by Donald Knuth on design and analysis of algorithms.
-
EATCS Bulletin eatcs.org
Surveys, tutorials, conferences reports, events, open problems and solutions, PhD Theses, and entertaining contributions.
-
European Association of TCS eatcs.org
-
Theory Announcements dmatheorynet.blogspot.com
DMANET spreads information on conferences, workshops, seminars etc. relating to discrete mathematics and algorithms.
-
ACM's students magazine special issue for theory of computation.
-
SIGACT News dl.acm.org
ACM's official theoretical computer science news feed.
-
Williamson & Shmoys. The Design of Approximation Algorithms designofapproxalgs.com
It includes greedy, local search algorithms, dynamic programming, linear and semidefinite programming, and randomization.
-
Deutsch. The Fabric of Reality: The Science of Parallel Universes and Its Implications daviddeutsch.org.uk
The Fabric of Reality presents a startlingly integrated, rational and optimistic world view – the result of taking seriously the deepest ideas of modern science and the philosophy of science.
-
Salamon's List cstheory.stackexchange.com
Selected Conferences.
-
TCS Stack Exchange cstheory.stackexchange.com
Research-oriented Q&A of theoretical computer science.
-
CS Theory Jobs cstheory-jobs.org
TCS Jobs announcements.
-
CS Theory Events Aggregator cstheory-events.org
An aggregator for CS theory workshops and schools.
-
Agrawal & Jaiswal. When Machine Learning Meets AI and Game Theory cs229.stanford.edu
.
-
Aspnes. Notes on Randomized Algorithms cs.yale.edu
Supplemental notes to the standard books by Mitzenmacher & Upfals, and Motwani & Raghavan.
-
Aspnes. Notes on Discrete Mathematics cs.yale.edu
Fall 2017 of the Yale course CPSC 202a, Mathematical Tools for Computer Science.
-
Watrous. Introduction to The Theory of Computing cs.uwaterloo.ca
undergrad introduction to theory of computation
-
First cs.ubc.ca
and Second Course in Randomized Algorithms. Columbia. - Respectively, undergrad and grad courses for probabilistic methods in algorithms.
-
-
Rubinstein & Weinberg. Research Masters in TCS cs.princeton.edu
A list of master programs in TCS.
-
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…
-
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)?
-
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…
-
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.
-
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.
-
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.
-
Koutsoupias. Probability and Computing. Oxford cs.ox.ac.uk
Introduction to probabilistic methods in computer science.
-
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.
-
Dinitz. Approximation Algorithms. Johns Hopkins cs.jhu.edu
It includes greedy, local search, dynamic programming, randomized rounding, tree embeddings, and semidefinite programming.
-
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.
- next page of items loading…
