The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
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Pattern Recognition and Machine Learning (Information Science and Statistics)
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Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning)
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Information Theory, Inference & Learning Algorithms
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Elements of Information Theory 2nd Edition (Wiley Series in Telecommunications and Signal Processing)
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Dynamic Programming and Optimal Control (2 Vol Set)
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Combinatorial Optimization: Algorithms and Complexity
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Matrix Analysis
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Nonlinear Programming
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Numerical Optimization (Springer Series in Operations Research and Financial Engineering)
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Convex Analysis (Princeton Landmarks in Mathematics and Physics)
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A First Course in Optimization Theory
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Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)
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Matrix Computations (Johns Hopkins Studies in Mathematical Sciences)(3rd Edition)
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Introduction to Linear Optimization (Athena Scientific Series in Optimization and Neural Computation, 6)
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The Elements of Statistical Learning
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Fundamentals of Wireless Communication
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