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NIPS
2001
13 years 11 months ago
A New Discriminative Kernel From Probabilistic Models
Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, ...
NIPS
2001
13 years 11 months ago
Risk Sensitive Particle Filters
We propose a new particle filter that incorporates a model of costs when generating particles. The approach is motivated by the observation that the costs of accidentally not trac...
Sebastian Thrun, John Langford, Vandi Verma
NIPS
2001
13 years 11 months ago
The Unified Propagation and Scaling Algorithm
In this paper we will show that a restricted class of constrained minimum divergence problems, named generalized inference problems, can be solved by approximating the KL divergen...
Yee Whye Teh, Max Welling
NIPS
2001
13 years 11 months ago
Information-Geometrical Significance of Sparsity in Gallager Codes
We report a result of perturbation analysis on decoding error of the belief propagation decoder for Gallager codes. The analysis is based on information geometry, and it shows tha...
Toshiyuki Tanaka, Shiro Ikeda, Shun-ichi Amari
NIPS
2001
13 years 11 months ago
Partially labeled classification with Markov random walks
To classify a large number of unlabeled examples we combine a limited number of labeled examples with a Markov random walk representation over the unlabeled examples. The random w...
Martin Szummer, Tommi Jaakkola
NIPS
2001
13 years 11 months ago
Bayesian time series classification
This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extract...
Peter Sykacek, Stephen J. Roberts
NIPS
2001
13 years 11 months ago
Transform-invariant Image Decomposition with Similarity Templates
Recent work has shown impressive transform-invariant modeling and clustering for sets of images of objects with similar appearance. We seek to expand these capabilities to sets of...
Chris Stauffer, Erik G. Miller, Kinh Tieu
NIPS
2001
13 years 11 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
NIPS
2001
13 years 11 months ago
Agglomerative Multivariate Information Bottleneck
The Information bottleneck method is an unsupervised non-parametric data organization technique. Given a joint distribution
Noam Slonim, Nir Friedman, Naftali Tishby