Programming Collective Intelligence: Building Smart Web 2.0 Applications
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Pattern Recognition and Machine Learning (Information Science and Statistics)
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The Elements of Statistical Learning
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Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)
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Algorithmic Game Theory
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Semi-Supervised Learning (Adaptive Computation and Machine Learning)
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The Minimum Description Length Principle (Adaptive Computation and Machine Learning)
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Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
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Computational Methods of Feature Selection (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)
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Time Series Prediction: Forecasting The Future And Understanding The Past (Proceedings Volume, Santa Fe Institute Studies in the Sciences of Complexity)
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Data Clustering: Theory, Algorithms, and Applications (ASA-SIAM Series on Statistics and Applied Probability)
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Complex Graphs and Networks (Cbms Regional Conference Series in Mathematics)
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Modern Multidimensional Scaling: Theory and Applications (Springer Series in Statistics)
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Information and Complexity in Statistical Modeling (Information Science and Statistics)
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Independent Component Analysis: A Tutorial Introduction (Bradford Books)
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Reasoning about Uncertainty
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Prediction, Learning, and Games
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Large-Scale Kernel Machines (Neural Information Processing)
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Mining Graph Data
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Kernel Methods in Computational Biology (Computational Molecular Biology)
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Algorithmic Learning in a Random World
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Learning Theory: An Approximation Theory Viewpoint (Cambridge Monographs on Applied and Computational Mathematics)
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