Introduction to Algorithms
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Pattern Recognition and Machine Learning (Information Science and Statistics)
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Artificial Intelligence: A Modern Approach (2nd Edition) (Prentice Hall Series in Artificial Intelligence)
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Elements of Information Theory 2nd Edition (Wiley Series in Telecommunications and Signal Processing)
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The Elements of Statistical Learning
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Computers and Intractability: A Guide to the Theory of NP-Completeness (Series of Books in the Mathematical Sciences)
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Algorithmic Game Theory
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Combinatorial Optimization: Algorithms and Complexity
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Introduction to Modern Cryptography: Principles and Protocols (Chapman & Hall/Crc Cryptography and Network Security Series)
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Machine Learning (Mcgraw-Hill International Edit)
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Information Theory, Inference & Learning Algorithms
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Approximation Algorithms
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Convex Optimization
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Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)
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Probability and Computing: Randomized Algorithms and Probabilistic Analysis
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Pattern Classification (2nd Edition)
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Machine Learning
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Foundations of Statistical Natural Language Processing
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Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition (Prentice Hall Series in Artificial Intelligence)
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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
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Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
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A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability)
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Prediction, Learning, and Games
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Learning in Graphical Models (Adaptive Computation and Machine Learning)
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Kernel Methods for Pattern Analysis
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Computational Learning Theory (Cambridge Tracts in Theoretical Computer Science)
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Foundations of Cryptography
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The Nature of Statistical Learning Theory (Information Science and Statistics)
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Neural Network Learning: Theoretical Foundations
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Communication Complexity
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Circuits of the Mind
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