MLRG - SPRING 2009

Date	Topic	Unit
January 23rd	Bring papers and topics!	Organizational
January 30th	Classification of anti-learnable biological and synthetic data Adam Kowalczyk (ECML/PKDD 2007) More anti-learning related links: http://users.rsise.anu.edu.au/~akowalczyk/antilearning.html	Intro
February 6th	Learning Gaussian Processes from Multiple Tasks Kai Yu, Volker Tresp, Anton Schwaighofer (ICML 2005)	Multi-task Learning
February 13rd	Learning Multiple Related Tasks using Latent Independent Component Analysis Jian Zhang, Zoubin Ghahramani, Yiming Yang (NIPS 2005)	Multi-task Learning
February 27th	Online Methods for Multi-Domain Learning and Adaptation Mark Dredze, Koby Crammer (EMNLP 2008)	Multi-task Learning
March 6th	Introduction to tensors Joakim Strandberg	High-dimensional Learning
March 13th	3D City Modeling based on Hidden Markov Model Florent Lafarge, Xavier Descombes, Josiane Zerubia, and Marc Pierrot-Deseilligny (ICIP 2007)	Intermission
March 20th	Tensor Subspace Analysis Xiaofei He, Deng Cai, Partha Niyogi1	High-dimensional Learning
March 27th	No meeting.
April 3rd	The Information-Form Data Association Filter Brad Schumitsch, Sebastian Thrun, Gary Bradski, Kunle Olukotun	High-dimensional Learning
April 10th	Hierarchical Sampling for Active Learning Sanjoy Dasgupta, Daniel Hsu	Active Learning
April 17th	Cascaded Classification Models: Combining Models for Holistic Scene Understanding Geremy Heitz, Stephen Gould, Ashutosh Saxena, Daphne Koller	Intermission
April 24th	Efficient Structure Learning of Markov Networks using L1-Regularization Su-In Lee, Varun Ganapahthi, Daphne Koller	Intermission
May 1st	A General Agnostic Active Learning Algorithm Sanjoy Dasgupta, Daniel Hsu, Claire Monteleoni	Active Learning
May 8th	VC Dimension tutorial Andrew Moore A Tutorial on Support Vector Machines for Pattern Recognition (section 2) Christopher Burges	Intermission
May 22nd	Structured Generative Models for Unsupervised Named-Entity Clustering (practice talk) Micha Elsner	Intermission