Recommender Systems: The Textbook
Charu C. Aggarwal
Non-Convex Optimization for Machine Learning
Prateek Jain & Purushottam Kar
Advanced Engineering Electromagnetics
Constantine A. Balanis
Probabilistic Graphical Models: Principles and Techniques
Daphne Koller & Nir Friedman
Entropy and Diversity: The Axiomatic Approach
Tom Leinster
How to Prove It: A Structured Approach
Daniel J. Velleman
Proofs and Refutations: The Logic of Mathematical Discovery
Imre Lakatos
The Design of Approximation Algorithms
David P. Williamson & David B. Shmoys
Information Theory, Inference and Learning Algorithms
David J. C. MacKay
Computer Vision: Models, Learning, and Inference
Simon J. D. Prince
Algorithms for Convex Optimization
Nisheeth K. Vishnoi
Filtering and System Identification: A Least Squares Approach
Michel Verhaegen & Vincent Verdult