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» Combining Learned Discrete and Continuous Action Models
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ICML
2009
IEEE
16 years 15 days ago
GAODE and HAODE: two proposals based on AODE to deal with continuous variables
AODE (Aggregating One-Dependence Estimators) is considered one of the most interesting representatives of the Bayesian classifiers, taking into account not only the low error rate...
Ana M. Martínez, José A. Gáme...
CVPR
2012
IEEE
13 years 2 months ago
Multi-view latent variable discriminative models for action recognition
Many human action recognition tasks involve data that can be factorized into multiple views such as body postures and hand shapes. These views often interact with each other over ...
Yale Song, Louis-Philippe Morency, Randall Davis
ANOR
2011
175views more  ANOR 2011»
14 years 6 months ago
Integrated exact, hybrid and metaheuristic learning methods for confidentiality protection
A vital task facing government agencies and commercial organizations that report data is to represent the data in a meaningful way and simultaneously to protect the confidentialit...
Fred Glover, Lawrence H. Cox, Rahul Patil, James P...
ECML
2006
Springer
15 years 3 months ago
Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
Scott Proper, Prasad Tadepalli
GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
15 years 3 months ago
Adaptive discretization for probabilistic model building genetic algorithms
This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable the probabilistic model building genetic algorithm (PMBGA) to solve optimization pro...
Chao-Hong Chen, Wei-Nan Liu, Ying-Ping Chen