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PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
13 years 7 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup
ICML
2004
IEEE
14 years 9 months ago
Lookahead-based algorithms for anytime induction of decision trees
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch
CVPR
2012
IEEE
11 years 11 months ago
A learning-based framework for depth ordering
Depth ordering is instrumental for understanding the 3D geometry of an image. We as humans are surprisingly good ordering even with abstract 2D line drawings. In this paper we pro...
Zhaoyin Jia, Andrew C. Gallagher, Yao-Jen Chang, T...
ACL
2000
13 years 10 months ago
A Unified Statistical Model for the Identification of English BaseNP
This paper presents a novel statistical model for automatic identification of English baseNP. It uses two steps: the Nbest Part-Of-Speech (POS) tagging and baseNP identification g...
Endong Xun, Changning Huang, Ming Zhou
ECCV
2004
Springer
14 years 10 months ago
Human Pose Estimation Using Learnt Probabilistic Region Similarities and Partial Configurations
Abstract. A model of human appearance is presented for efficient pose estimation from real-world images. In common with related approaches, a high-level model defines a space of co...
Timothy J. Roberts, Stephen J. McKenna, Ian W. Ric...