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ICML
2009
IEEE
16 years 12 days ago
A stochastic memoizer for sequence data
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Frank Wood, Cédric Archambeau, Jan Gasthaus...
ICML
2005
IEEE
16 years 12 days ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
JMLR
2008
110views more  JMLR 2008»
14 years 11 months ago
Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods
We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...
Matthias W. Seeger
JMLR
2006
124views more  JMLR 2006»
14 years 11 months ago
Policy Gradient in Continuous Time
Policy search is a method for approximately solving an optimal control problem by performing a parametric optimization search in a given class of parameterized policies. In order ...
Rémi Munos
ICML
2008
IEEE
16 years 12 days ago
An HDP-HMM for systems with state persistence
The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...