awesome-theoretical-computer-science

It examines the relevance of modern theoretical computer science to traditional questions in philosophy, and conversely, what philosophy can contribute to theoretical computer science.

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)?

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 encryption); and efficient algorithms (genomic sequencing).

A modern, brief, and accessible text which introduces theoretical computer science for undergrads. It includes topics not usually included in standard undergrad text-books.

The basic theory underlying machine learning and the process of generalizing from data.

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.

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.

A story about people, pioneers with diverse backgrounds and characters who established a new field.

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.

A nontechnical introduction to P-NP, its rich history, and its algorithmic implications for everything we do with computers and beyond.

It argues that computational complexity theory leads to new perspectives on the nature of mathematical knowledge and other philosophical questions.

It describes how quantum mechanics can be tested in the limit of high complexity regime by extending the usual scientific paradigm to include.

Collected works in celebration of Laszlo Lovasz, Connecting discrete math with computer science.

A historical overview of computational complexity.

It explains the remarkable work of Shafi and Silvio and their works' implications on foundations of cryptography.

Classic papers by thinkers ranging from Aristotle and Leibniz to Norbert Wiener and Gordon Moore that chart the evolution of computer science.

Researchers, practitioners and innovators who are at the intersection of research and practice, sharing their experiences, lessons, visions for the future.

Interviews with eminent figures in Berkeley.

Donald Knuth 2Silvio MicaliRichard KarpScott Aaronson 1Scott Aaronson 2

A classic math-oriented introduction to computer science.

Notably uses ideas such as randomness, approximation, high dimensional geometry. Faces uncertainty, approaches to handle big data, handling intractability, heuristic approaches, ..etc.

Semantic tableaux are used because they are theoretically sound and easy to understand.

A series dedicated to math topics and their relevance to computer science.

A junior introduction to discrete mathematics for computer scientists. -

A second course on algorithms and data structures. — added by Erik himself!

Freely available lecture notes on mathematics.