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AAAI
2012
13 years 2 months ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous
97
Voted
ATAL
2009
Springer
14 years 10 months ago
Learning to Locate Trading Partners in Agent Networks
This paper is motivated by some recent, intriguing research results involving agent-organized networks (AONs). In AONs, nodes represent agents, and collaboration between nodes are...
John Porter, Kuheli Chakraborty, Sandip Sen
CVPR
2011
IEEE
14 years 9 months ago
Learning Effective Human Pose Estimation from Inaccurate Annotation
The task of 2-D articulated human pose estimation in natural images is extremely challenging due to the high level of variation in human appearance. These variations arise from di...
Sam Johnson, Mark Everingham
114
Voted
CVPR
2011
IEEE
14 years 8 months ago
Learning Temporally Consistent Rigidities
We present a novel probabilistic framework for rigid tracking and segmentation of shapes observed from multiple cameras. Most existing methods have focused on solving each of thes...
Jean-Sebastien Franco, Edmond Boyer
JMLR
2012
13 years 2 months ago
Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...
Avneesh Singh Saluja, Priya Krishnan Sundararajan,...