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145
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NIPS
2003
15 years 5 months ago
Approximate Expectation Maximization
We discuss the integration of the expectation-maximization (EM) algorithm for maximum likelihood learning of Bayesian networks with belief propagation algorithms for approximate i...
Tom Heskes, Onno Zoeter, Wim Wiegerinck
156
Voted
NIPS
2003
15 years 5 months ago
Markov Models for Automated ECG Interval Analysis
We examine the use of hidden Markov and hidden semi-Markov models for automatically segmenting an electrocardiogram waveform into its constituent waveform features. An undecimated...
Nicholas P. Hughes, Lionel Tarassenko, Stephen J. ...
NIPS
2003
15 years 5 months ago
Semi-Supervised Learning with Trees
We describe a nonparametric Bayesian approach to generalizing from few labeled examples, guided by a larger set of unlabeled objects and the assumption of a latent tree-structure ...
Charles Kemp, Thomas L. Griffiths, Sean Stromsten,...
141
Voted
NIPS
2003
15 years 5 months ago
An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science
Despite the popularity of connectionist models in cognitive science, their performance can often be difficult to evaluate. Inspired by the geometric approach to statistical model ...
Woojae Kim, Daniel J. Navarro, Mark A. Pitt, In Ja...
92
Voted
NIPS
2003
15 years 5 months ago
Identifying Structure across Pre-partitioned Data
We propose an information-theoretic clustering approach that incorporates a pre-known partition of the data, aiming to identify common clusters that cut across the given partition...
Zvika Marx, Ido Dagan, Eli Shamir