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109
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IROS
2009
IEEE
132views Robotics» more  IROS 2009»
15 years 7 months ago
Automatic selection of task spaces for imitation learning
Abstract— Previous work [1] shows that the movement representation in task spaces offers many advantages for learning object-related and goal-directed movement tasks through imit...
Manuel Mühlig, Michael Gienger, Jochen J. Ste...
88
Voted
ICPR
2008
IEEE
15 years 7 months ago
Semi-supervised learning by locally linear embedding in kernel space
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
Rujie Liu, Yuehong Wang, Takayuki Baba, Daiki Masu...
CEC
2003
IEEE
15 years 4 months ago
Playing in continuous spaces: some analysis and extension of population-based incremental learning
- As an alternative to traditional Evolutionary Algorithms (EAs), Population-Based Incremental Learning (PBIL) maintains a probabilistic model of the best individual(s). Originally...
Bo Yuan, Marcus Gallagher
ETRA
2010
ACM
176views Biometrics» more  ETRA 2010»
15 years 7 months ago
Learning relevant eye movement feature spaces across users
In this paper we predict the relevance of images based on a lowdimensional feature space found using several users’ eye movements. Each user is given an image-based search task,...
Zakria Hussain, Kitsuchart Pasupa, John Shawe-Tayl...
IROS
2007
IEEE
123views Robotics» more  IROS 2007»
15 years 7 months ago
Reinforcement learning in multi-dimensional state-action space using random rectangular coarse coding and Gibbs sampling
: This paper presents a coarse coding technique and an action selection scheme for reinforcement learning (RL) in multi-dimensional and continuous state-action spaces following con...
Kimura Kimura