CS269: Machine Learning Theory Lecture 16: SVMs and Kernels November 17, 2010 Lecturer: Jennifer Wortman Vaughan Scribe: Jason Au, Ling Fang, Kwanho Lee Today, we will continue on the topic of support vector machines, fi

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Using Markov Decision Theory to Provide a Fair Challenge in a Roll-and-Move Board Game ´ Eric Beaudry, Francis Bisson, Simon Chamberland and Froduald Kabanza various means. For example, artificial players may have a

Source URL: game.itu.dk

• Dynamic programming
• Markov processes
• Mathematical optimization
• Mathematical analysis
• Probability theory
• Systems theory
• Operations research
• Equations
• Markov decision process
• Bellman equation
• Markov chain
• Reinforcement learning

In Gerhard Lakemeyer and Bernhard Nebel, editors, Exploring Artificial Intelligence in the New Millenium, Morgan Kaufmann, 2002. Learning Theory and Language Modeling David McAllester

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CS269: Machine Learning Theory Lecture 11: Regularization in Online Learning November 1, 2010 Lecturer: Jennifer Wortman Vaughan Scribe: Jerry Weng, Li Yang Ku

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Evidence-Specific Structures for Rich Tractable CRFs Carlos Guestrin Carnegie Mellon University

Source URL: select.cs.cmu.edu

• Graph theory
• Graphical models
• Machine learning
• Artificial intelligence
• Learning
• Statistical models
• Conditional random field
• Bayesian network
• Tree decomposition
• Treewidth
• Markov random field
• Expectationmaximization algorithm

Detecting and classifying anomalous behavior in spatiotemporal network data∗ William Chad Young Joshua E. Blumenstock

Source URL: www.jblumenstock.com

• Markov models
• Machine learning
• Probability theory
• Artificial intelligence
• Hidden Markov model
• Markov chain
• Speech recognition
• Forwardbackward algorithm

Survey of Principles of Connected Learning I1. Think of an activity that: You enjoy doing You do with other people You get better at doing, the more you engage in the activity

Source URL: researchtools.dmlhub.net

• Physical chemistry
• Thermodynamic activity
• Happiness
• Philosophy
• Nature
• Agree to disagree
• Activity theory

Journal of Machine Learning Research1561 Submitted 8/09; Revised 3/10; Published 4/10 Hilbert Space Embeddings and Metrics on Probability Measures Bharath K. Sriperumbudur

Source URL: select.cs.cmu.edu

• Mathematical analysis
• Mathematics
• Analysis
• Hilbert space
• Fourier analysis
• Generalized functions
• Functional analysis
• Operator theory
• Reproducing kernel Hilbert space
• Positive-definite kernel
• Dirac delta function
• Convolution

CS269: Machine Learning Theory Lecture 17: Learning from Labeled and Unlabeled Data November 22, 2010 Lecturer: Jennifer Wortman Vaughan Scribe: Georgios Georgiadis, Ryan R. Rosario, Alan Roytman

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