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» Learning to Walk through Imitation
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MIR
2005
ACM
140views Multimedia» more  MIR 2005»
14 years 3 months ago
Multiple random walk and its application in content-based image retrieval
In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
Jingrui He, Hanghang Tong, Mingjing Li, Wei-Ying M...
FOCS
1994
IEEE
14 years 1 months ago
The Power of Team Exploration: Two Robots Can Learn Unlabeled Directed Graphs
We show that two cooperating robots can learn exactly any strongly-connected directed graph with n indistinguishable nodes in expected time polynomial in n. We introduce a new typ...
Michael A. Bender, Donna K. Slonim
ICAD
2004
13 years 11 months ago
Interaction Sound Feedback in a Haptic Virtual Environment to Improve Motor Skill Acquisition
This paper describes the concept and the realisation of a research prototype of a haptic environment that is enhanced with sound feedback to impart implicit knowledge and to teach...
Christian Müller-Tomfelde
ICRA
2010
IEEE
170views Robotics» more  ICRA 2010»
13 years 8 months ago
Categorizing object-action relations from semantic scene graphs
— In this work we introduce a novel approach for detecting spatiotemporal object-action relations, leading to both, action recognition and object categorization. Semantic scene g...
Eren Erdal Aksoy, Alexey Abramov, Florentin Wö...
ATAL
2007
Springer
14 years 1 months ago
Confidence-based policy learning from demonstration using Gaussian mixture models
We contribute an approach for interactive policy learning through expert demonstration that allows an agent to actively request and effectively represent demonstration examples. I...
Sonia Chernova, Manuela M. Veloso