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» A theory of learning with similarity functions
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IJCAI
2007
15 years 3 months ago
Utile Distinctions for Relational Reinforcement Learning
We introduce an approach to autonomously creating state space abstractions for an online reinforcement learning agent using a relational representation. Our approach uses a tree-b...
William Dabney, Amy McGovern
FLAIRS
2004
15 years 3 months ago
State Space Reduction For Hierarchical Reinforcement Learning
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
Mehran Asadi, Manfred Huber
AIEDU
2007
77views more  AIEDU 2007»
15 years 1 months ago
Desirable Characteristics of Learning Companions
This study investigated the desirable characteristics of anthropomorphized learning-companion agents for college students. First, interviews with six undergraduates explored their ...
Yanghee Kim
ICCV
2009
IEEE
16 years 6 months ago
Weakly supervised discriminative localization and classification: a joint learning process
Visual categorization problems, such as object classification or action recognition, are increasingly often approached using a detection strategy: a classifier function is first ...
Minh Hoai Nguyen, Lorenzo Torresani, Fernando de l...
ICIP
2007
IEEE
16 years 3 months ago
Large Scale Learning of Active Shape Models
We propose a framework to learn statistical shape models for faces as piecewise linear models. Specifically, our methodology builds upon primitive active shape models(ASM) to hand...
Atul Kanaujia, Dimitris N. Metaxas