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» Bayesian Learning of Markov Network Structure
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NIPS
1994
13 years 9 months ago
An Input Output HMM Architecture
We introduce a recurrent architecture having a modular structure and we formulate a training procedure based on the EM algorithm. The resulting model has similarities to hidden Ma...
Yoshua Bengio, Paolo Frasconi
ENGL
2007
102views more  ENGL 2007»
13 years 7 months ago
Decision Theoretic Agent Design for Personal Rapid Transit Systems
—This paper details a learning decision-theoretic intelligent agent designed to solve the problem of guiding vehicles in the context of Personal Rapid Transit (PRT). The intellig...
Iheanyi C. Umez-Eronini, Ferat Sahin
ICRA
2008
IEEE
208views Robotics» more  ICRA 2008»
14 years 2 months ago
Unsupervised body scheme learning through self-perception
— In this paper, we present an approach allowing a robot to learn a generative model of its own physical body from scratch using self-perception with a single monocular camera. O...
Jürgen Sturm, Christian Plagemann, Wolfram Bu...
BMCBI
2006
118views more  BMCBI 2006»
13 years 7 months ago
Predicting the effect of missense mutations on protein function: analysis with Bayesian networks
Background: A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, ...
Chris J. Needham, James R. Bradford, Andrew J. Bul...
ICML
2007
IEEE
14 years 8 months ago
Comparisons of sequence labeling algorithms and extensions
In this paper, we survey the current state-ofart models for structured learning problems, including Hidden Markov Model (HMM), Conditional Random Fields (CRF), Averaged Perceptron...
Nam Nguyen, Yunsong Guo