Non-Convex Optimization for Machine Learning
Prateek Jain & Purushottam Kar
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
Stefano V. Albrecht & Filippos Christianos & Lukas Schäfer
Entropy and Diversity: The Axiomatic Approach
Tom Leinster
Everything You Always Wanted To Know About Mathematics
Brendan W. Sullivan
Proofs and Refutations: The Logic of Mathematical Discovery
Imre Lakatos
Information Theory, Inference and Learning Algorithms
David J. C. MacKay
Computer Vision: Models, Learning, and Inference
Simon J. D. Prince
How to Prove It: A Structured Approach
Daniel J. Velleman
Filtering and System Identification: A Least Squares Approach
Michel Verhaegen & Vincent Verdult
Algorithms for Convex Optimization
Nisheeth K. Vishnoi
The Design of Approximation Algorithms
David P. Williamson & David B. Shmoys