Title: Deep Learning, Author: Ian Goodfellow
Title: The Elements of Statistical Learning: Data Mining, Inference, and Prediction / Edition 2, Author: Trevor Hastie
Title: Pattern Recognition and Machine Learning / Edition 1, Author: Christopher M. Bishop
Title: Prediction, Learning, and Games, Author: Nicolo Cesa-Bianchi
Title: Optimal Learning / Edition 1, Author: Warren B. Powell
Title: Bayesian Reasoning and Machine Learning, Author: David Barber
Title: Scaling up Machine Learning: Parallel and Distributed Approaches, Author: Ron Bekkerman
Title: Kernel Methods for Pattern Analysis / Edition 1, Author: John Shawe-Taylor
Title: Applications of Learning Classifier Systems / Edition 1, Author: Larry Bull
Title: Deep Learning Neural Networks: Design And Case Studies, Author: Daniel Graupe
Title: Learning with Uncertainty / Edition 1, Author: Xizhao Wang
Title: Information Theoretic Learning: Renyi's Entropy and Kernel Perspectives / Edition 1, Author: Jose C. Principe
Title: Brain and Perception: Holonomy and Structure in Figural Processing / Edition 1, Author: Karl H. Pribram
Title: Self-Adaptive Systems for Machine Intelligence / Edition 1, Author: Haibo He
Title: Adaptivity and Learning: An Interdisciplinary Debate / Edition 1, Author: Reimer Kïhn
Title: Machine Learning in Bioinformatics / Edition 1, Author: Yanqing Zhang
Title: Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability / Edition 1, Author: Danilo P. Mandic
Title: Advances in Bayesian Networks / Edition 1, Author: José A. Gámez
Title: Computational Trust Models and Machine Learning / Edition 1, Author: Xin Liu
Title: Transfer Learning / Edition 1, Author: Qiang Yang

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