Machine Learning
and Friends at CMU

The 2001 ML talks:

December 3		CALD Seminar scheduled. To be held from 12:30-2:00pm in NSH 3305. (With Pizza) Kevin Kelly (CMU), Ockham's Razor Deduced from Error Minimization
November 26		Drew Bagnell, Integrating Scope into Learning with Application to Information Extraction Aaron Courville, Modeling Temporal Structure in Classical Conditioning This seminar took place in Wean Hall 7220 at 1:30 pm
November 19		Vandi Verma, Risk Sensitive Particle Filters, Paper Guy Lebanon, Boosting and Maximum Likelihood for Exponential Models, Tech Report
November 12		John Langford, Provable Learning, Slides
November 5		Geoff Gordon, Variations on a Particle Filter, Slides
September 24		ICML / KDD / COLT Review Session, Shuchi Chawla, John Langford, Ricardo Silva, and Martin Zinkevich presented
July 23		Douglas Aberdeen (Australian National University), Gradient Reinforcement Learning of POMDP Policy Graphs, Slides
July 16		Peter Venable, Lynx: Building a Statistical Parser from a Rule-Based Parser
June 26		Dan Pelleg, Mixtures of Rectangles: Interpretable Soft Clustering Rayid Ghani, Hypertext Categorization using Hyperlink Patterns and Meta Data
June 4		Chuck Rosenberg, Color Constancy Using KL-Divergence
March 26		Bryan Singer, Learning to Generate Fast Signal Processing Implementations, Slides
March 19		Andrew McCallum, Efficient Clustering of High-Dimensional Data Sets with Application to Reference Matching
March 12		John Langford, The Usefulness of Sample Complexity Bounds, Slides
February 19		Malcolm Strens, Reinforcement Learning Methods for Military Applications, Slides, ppt slides
February 12		Frank Dellaert, Structure from Motion without Correspondence, Slides, ppt slides
February 5		NIPS Review, Geoff Gordon, Joelle Pineau, John Langford, and Tom Minka made presentations and here are their Slides.
January 24		Faculty Candidate talk scheduled. Sam T. Roweis (University College of London), Scalable Learning of Nonlinear Manifolds from Data
January 22		CALD Seminar scheduled. Thorsten Joachims (GMD), The Maximum-Margin Approach to Learning Text Classifiers
January 15		SCS Distinguished Seminar scheduled. Steve Smale (City University of Hong Kong), On the Mathematical Foundations of Learning Theory