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JETAI
2002
69views more  JETAI 2002»
15 years 2 months ago
The interaction of representations and planning objectives for decision-theoretic planning tasks
We study decision-theoretic planning or reinforcement learning in the presence of traps such as steep slopes for outdoor robots or staircases for indoor robots. In this case, achi...
Sven Koenig, Yaxin Liu
140
Voted
ICIP
2007
IEEE
16 years 5 months ago
Fast Detection of Independent Motion in Crowds Guided by Supervised Learning
Different from appearance-based methods, clustering feature points only by their motion coherence is an emerging category of approach to detecting and tracking individuals among c...
Yuan Li, Haizhou Ai
133
Voted
CVPR
2008
IEEE
16 years 5 months ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...
147
Voted
IJCV
2011
264views more  IJCV 2011»
14 years 10 months ago
Cost-Sensitive Active Visual Category Learning
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...
Sudheendra Vijayanarasimhan, Kristen Grauman
FOCS
1990
IEEE
15 years 7 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum