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ICML
2009
IEEE
16 years 7 months ago
A majorization-minimization algorithm for (multiple) hyperparameter learning
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng
ICML
2009
IEEE
16 years 7 months ago
Binary action search for learning continuous-action control policies
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
Jason Pazis, Michail G. Lagoudakis
ICML
2007
IEEE
16 years 7 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney
ICML
2008
IEEE
16 years 7 months ago
Fast solvers and efficient implementations for distance metric learning
In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed framework for distance metric lear...
Kilian Q. Weinberger, Lawrence K. Saul
ICML
1999
IEEE
16 years 7 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox