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A comprehensive update of the leading algorithms text, with new material on matchings in bipartite graphs, online algorithms, machine learning, and other topics. Some books on …
A highly accessible, step-by-step introduction to deep learning, written in an engaging, question-and-answer style. The Little Learner introduces deep learning from the bottom up, …
A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. …
How global workers, influencers, and activists develop tactics of algorithmic resistance by appropriating and repurposing the same algorithms that control our lives. Algorithms are …
A clear, comprehensive, and rigorous introduction to the theory of computation. What is computable? What leads to efficiency in computation? Computability and Complexity offers a …
Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets. Human-centered data science is a …
Fundamental theory and practical algorithms of weakly supervised classification, emphasizing an approach based on empirical risk minimization. Standard machine learning techniques …
A comprehensive introduction to automata theory that uses the novel approach of viewing automata as data structures. This textbook presents automata theory from a fresh viewpoint …