Abstract | PDF
Bozhena Bidyuk, and Rina Dechter. "An Empirical Study of w-Cutset Sampling for Bayesian Networks". .In Uncertainty in AI, UAI-2003

Abstract | PostScript | PDF
Bozhena Bidyuk, and Rina Dechter. "Cycle-Cutset sampling for Bayesian Networks", to be published in the Canadian AI conerence, June 2003.

Thomas Hofmann,   Lijuan Cai,  and Massimiliano Ciaramita,"Learning with Taxonomies: Classifying Documents and Words," Workshop on Syntax, Semantics, and Statistics, Neural Information Processing (NIPS), pdf

All of the papers below can be found here


Leon Bottou, Yann LeCun,
Large Scale Online Learning

Charles C. Kemp, Thomas L. Griffiths, Sean Stromsten, Joshua B. Tenenbaum
Semi-Supervised Learning with Trees

Ting Liu, Andrew W. Moore, Alex Gray
"New Algorithms for Efficient High Dimensional Non-parametric Classification

Deva Ramanan, David A. Forsyth
"Automatic Annotation of Everyday Movements

Leonid Sigal, Michael Isard, Benjamin H. Sigelman, Michael J. Black
Attractive People: Assembling Loose-Limbed Models using Non-parametric
Belief Propagation

Marian S. Bartlett, Gwen Litttlewort, Ian Fasel, Joel Chenu, Takayuki
Kanda, Hiroshi Ishiguro, Javier R. Movellan
Towards Social Robots: Automatic Evaluation of Human-Robot Interaction
by Facial Expression Classification

Francis R. Bach, Michael I. Jordan
Learning Spectral Clustering

Neil D. Lawrence
Gaussian Process Latent Variable Models for Visualisation of High
Dimensional Data

XuanLong Nguyen, Michael I. Jordan
On the Concentration of Expectation and Approximate Inference in Layered
Networks

Alex J. Smola, S. V. N. Vishwanathan, Eleazar Eskin
Laplace Propagation

Volker Roth, Tilman Lange
Feature Selection in Clustering Problems

Victor Lavrenko, Raghavan Manmatha, Jiwoon Jeon
A Model for Learning the Semantics of Pictures