BIG DATA: SUPERVISED LEARNING LAB APPLICATION: SPAM FILTERING Vibhav Gogate The University of Texas at Dallas

Source URL: www.hlt.utdallas.edu

Noise-Tolerant Learning, the Parity Problem, and the Statistical Query Model AVRIM BLUM, ADAM KALAI, AND HAL WASSERMAN Carnegie Mellon University, Pittsburgh, Pennsylvania Abstract. We describe a slightly subexponential

Source URL: research.microsoft.com

• Computational learning theory
• Machine learning
• Artificial intelligence
• Learning
• Probability distribution
• Theoretical computer science
• Probably approximately correct learning
• Statistical classification
• Error Tolerance
• Supervised learning

Hybrid Reinforcement/Supervised Learning for Dialogue Policies from COMMUNICATOR data James Henderson and Oliver Lemon and Kallirroi Georgila School of Informatics University of Edinburgh 2 Buccleuch Place, Edinburgh EH8

Source URL: cui.unige.ch

Revisiting Embedding Features for Simple Semi-supervised Learning † Jiang Guo† , Wanxiang Che† , Haifeng Wang‡ , Ting Liu†∗ Research Center for Social Computing and Information Retrieval Harbin Institute of T

Source URL: ir.hit.edu.cn

Adaptive Road Following using Self-Supervised Learning and Reverse Optical Flow David Lieb, Andrew Lookingbill, and Sebastian Thrun Stanford Artificial Intelligence Laboratory Stanford University Gates Hall 1A; 355 Serra

Source URL: www.roboticsproceedings.org

Asymptotic Analysis of Generative Semi-Supervised Learning Joshua V. Dillon Krishnakumar Balasubramanian

Source URL: theanalysisofdata.com

Finite sample analysis of semi-supervised learning Technical Report ECEAarti Singh, Robert D. Nowak Department of Electrical and Computer Engineering University of Wisconsin - Madison

Source URL: nowak.ece.wisc.edu

Interlinking: Performance Assessment of User Evaluation vs. Supervised Learning Approaches Mofeed Hassan Jens Lehmann

Source URL: events.linkeddata.org

Today • Supervised Learning Introduction to Artificial Intelligence

Source URL: www.cs.du.edu

Distributional Semantics Beyond Words: Supervised Learning of Analogy and Paraphrase Peter D. Turney National Research Council Canada Information and Communications Technologies Ottawa, Ontario, Canada, K1A 0R6

Source URL: aclweb.org