Machine Learning
and Friends at CMU

The 2006 Spring ML talks:

December 04		Dave Tolliver, Spectral Partitioning: approximations, image processing and clustering.
November 20		Tom Mitchell, Machine Learning and Human Learning.
November 13		Anton Chechetka, Online Decoding of Markov Models under Latency Constraints.
November 06		Nathan Ratliff, Boosting Structured Prediction for Imitation Learning.
October 30		Jason Ernst, Learning Dynamic Maps of Temporal Gene Regulation.
October 16		Alice Zheng, Statistical Software Debugging.
October 02		KDD 2006 Conference Review Session. Hanghang Tong, Center-Piece Subgraphs: Problem Definition and Fast Solutions. Jimeng Sun, Beyond Streams and Graphs: Dynamic Tensor Analysis.
September 25		Leonid Teverovskiy, Learning-based Deformable Neuroimage Registration.
September 18		UAI 2006 Conference Review Session. Andreas Krause, Non-Minimal Triangulations for Mixed Stochastic/Deterministic Graphical Models. Pradeep Ravikumar, On the Number of Samples Needed to Learn the Correct Structure of a Bayesian Network.
September 11		ICML 2006 Conference Review Session. Francisco Pereira, Support Vector Decomposition Machine. Steve Hanneke, Inference with the Universum. Kyung-Ah Sohn, Bayesian Multi-Population Haplotype Inference via a Hierarchical Dirichlet Process Mixture.
May 08		Ramesh Nallapati, Smoothed Dirichlet distribution: Understanding the Cross-entropy ranking function in Information Retrieval.
April 17		Ricardo Silva, Bayesian Inference for Gaussian Mixed Graph Models.
April 03		Larry Wasserman, Rodeo: Sparse Nonparametric Regression in High Dimensions.
March 27		Alice Zheng, Dynamic Contextual Friendship Networks. (Venue: Wean Hall 5409)
February 27		Michael Benisch, Machine Learning in TAC SCM (Trading Agent Competition in Supply Chain Management).
February 13		Probabilistic Graphical Models Session. Ryan Kerekes, Graphical model approach to Iris matching under local shifts and occlusions. Jun Yang, Exponential Family Harmoniums for Classifying Video Data. Purnamrita Sarkar, Euclidean Embedding of Author-Word Co-occurrence Data Through Time.
January 30		NIPS 2005 Conference Review Session. Brent Bryan, Active Learning For Identifying Function Threshold Boundaries. Brigham Andersen, Efficient Value of Information for Graphical Models. Pradeep Ravikumar, Preconditioner Approximations for Probabilistic Graphical Models.
January 23		NIPS 2005 Conference Review Session. Pradeep Ravikumar, Generalization in Clustering with Unobserved Features. Andreas Krause, Robust design of biological experiments. Daniel Neill, A Bayesian Spatial Scan Statistic.

The 2006 ML talks were organized by Edoardo Airoldi, Anna Goldenberg, Leonid Kontorovich, Andreas Krause and Pradeep Ravikumar.