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Huang, Te-Ming. author.
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supervised, semi-supervised and unsupervised machine learning collectively. The book presents both the theory
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Learning and Data Mining -- Research Contributions -- Learning to Detect Malicious Executables -- Data
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Reinforcement Learning -- Belief Selection in Point-Based Planning Algorithms for POMDPs -- Supervised and
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Reviews -- Using Semi-supervised Learning for Question Classification -- Query Similarity Computing Based
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Analysis -- A Sentence Compression Module for Machine-Assisted Subtitling -- Application of Semi-supervised
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Supervised Learning -- Comparing Meta-learning Algorithms -- A New Linear Dimensionality Reduction Technique
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