|
10
|
Linear Gaussian models for speech recognition
– Antti-Veikko Ilmari Rosti
- 2004
|
|
16
|
Locally Bayesian Learning with Applications to Retrospective Revaluation and Highlighting
– John K. Kruschke
- 2006
|
|
27
|
Classification and Regression using Mixtures of Experts
– Steven Richard Waterhouse
- 1997
|
|
1
|
ConneCtions Between Computational and neuroBiologiCal perspeCtives on decision making -- decision theory, . . .
– Peter Dayan, et al.
- 2008
|
|
7
|
An Introduction to Variational Methods for Graphical Methods
– Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, Lawrence K. Saul
- 1998
|
|
27
|
Variational bayesian learning of directed graphical models with hidden variables, Bayesian Analysis 1
– Matthew J. Beal, Zoubin Ghahramani
- 2006
|
|
27
|
Graphical Models and Variational Methods
– Zoubin Ghahramani, Matthew J. Beal, London England
- 2001
|
|
|
Some Methods for Training Mixtures of Experts
– Perry Moerland
- 1997
|
|
16
|
Accelerating cyclic update algorithms for parameter estimation by pattern searches
– Antti Honkela, Harri Valpola, Juha Karhunen
|
|
21
|
Ensemble learning in Bayesian neural networks
– David Barber, Christopher M. Bishop
- 1998
|
|
1
|
Divide and Conquer: Pattern Recognition using Mixtures of Experts
– Steve Waterhouse, Steve Waterhouse
- 1997
|
|
14
|
Unsupervised learning
– Zoubin Ghahramani
- 2004
|
|
1
|
Bethe Free Energy and Contrastive Divergence Approximations for Undirected Graphical Models
– Yee Whye Teh, Yee Whye Teh
- 2003
|
|
393
|
Dynamic Bayesian Networks: Representation, Inference and Learning
– Kevin Patrick Murphy
- 2002
|
|
5
|
Reinforcement learning for factored markov decision processes
– Brian Sallans
- 2002
|
|
7
|
Exponential family predictive representations of state
– David Wingate
|
|
19
|
Nonparametric Bayesian Models of Lexical Acquisition
– Sharon J. Goldwater
- 2007
|
|
37
|
Switching State-Space Models
– Zoubin Ghahramani, Geoffrey E. Hinton
- 1996
|
|
|
Continuous-state Graphical Models for . . .
– Leonid Sigal
- 2008
|
