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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Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
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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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Introduction to Machine Learning (Adaptive Computation and Machine Learning)
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Machine Learning (Mcgraw-Hill International Edit)
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Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
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Dynamic Programming and Optimal Control (2 Vol Set)
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Information Theory, Inference & Learning Algorithms
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Convex Optimization
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Dynamic Programming
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Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)
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Information Extraction: Algorithms and Prospects in a Retrieval Context (The Information Retrieval Series)
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Pattern Classification (2nd Edition)
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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
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Machine Learning
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Approximate Dynamic Programming: Solving the Curses of Dimensionality (Wiley Series in Probability and Statistics)
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Semi-Supervised Learning (Adaptive Computation and Machine Learning)
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Neural Networks for Pattern Recognition
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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
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Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
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Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems
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Learning Bayesian Networks (Artificial Intelligence)
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Neuro-Dynamic Programming (Optimization and Neural Computation Series, 3)
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The Minimum Description Length Principle (Adaptive Computation and Machine Learning)
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Markov Decision Processes: Discrete Stochastic Dynamic Programming (Wiley Series in Probability and Statistics)
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Prediction, Learning, and Games
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Computational Methods of Feature Selection (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)
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Kernel Methods for Pattern Analysis
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The Nature of Statistical Learning Theory (Information Science and Statistics)
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Large-Scale Kernel Machines (Neural Information Processing)
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Handbook of Learning and Approximate Dynamic Programming (IEEE Press Series on Computational Intelligence)
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Stochastic Learning and Optimization: A Sensitivity-Based Approach (International Series on Discrete Event Dynamic Systems)
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Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning (Operations Research/Computer Science Interfaces Series)
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Iterative Solution of Nonlinear Equations in Several Variables (Classics in Applied Mathematics, 30) (Classics in Applied Mathematics)
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