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» Factorial Learning and the EM Algorithm
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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
JMLR
2006
143views more  JMLR 2006»
13 years 7 months ago
Segmental Hidden Markov Models with Random Effects for Waveform Modeling
This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...
Seyoung Kim, Padhraic Smyth
COGSCI
2007
99views more  COGSCI 2007»
13 years 7 months ago
Language Evolution by Iterated Learning With Bayesian Agents
Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that la...
Thomas L. Griffiths, Michael L. Kalish
PCI
2005
Springer
14 years 1 months ago
Gossip-Based Greedy Gaussian Mixture Learning
Abstract. It has been recently demonstrated that the classical EM algorithm for learning Gaussian mixture models can be successfully implemented in a decentralized manner by resort...
Nikos A. Vlassis, Yiannis Sfakianakis, Wojtek Kowa...
UAI
2003
13 years 9 months ago
On the Convergence of Bound Optimization Algorithms
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...