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» A Bayesian Framework for Reinforcement Learning
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IROS
2008
IEEE
211views Robotics» more  IROS 2008»
14 years 2 months ago
GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Jonathan Ko, Dieter Fox
ICPR
2010
IEEE
13 years 5 months ago
Boosting Bayesian MAP Classification
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...
PAMI
2006
233views more  PAMI 2006»
13 years 7 months ago
Model-Based Hand Tracking Using a Hierarchical Bayesian Filter
This paper sets out a tracking framework, which is applied to the recovery of threedimensional hand motion from an image sequence. The method handles the issues of initialization,...
Björn Stenger, Arasanathan Thayananthan, Phil...
ICML
2010
IEEE
13 years 8 months ago
Internal Rewards Mitigate Agent Boundedness
Abstract--Reinforcement learning (RL) research typically develops algorithms for helping an RL agent best achieve its goals-however they came to be defined--while ignoring the rela...
Jonathan Sorg, Satinder P. Singh, Richard Lewis
UAI
2000
13 years 9 months ago
Gaussian Process Networks
In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different c...
Nir Friedman, Iftach Nachman