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122
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ECML
2006
Springer
15 years 7 months ago
An Efficient Approximation to Lookahead in Relational Learners
Abstract. Greedy machine learning algorithms suffer from shortsightedness, potentially returning suboptimal models due to limited exploration of the search space. Greedy search mis...
Jan Struyf, Jesse Davis, C. David Page Jr.
ECCV
2008
Springer
16 years 5 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
140
Voted
JMLR
2010
134views more  JMLR 2010»
14 years 10 months ago
Using Contextual Representations to Efficiently Learn Context-Free Languages
We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. W...
Alexander Clark, Rémi Eyraud, Amaury Habrar...
IROS
2009
IEEE
150views Robotics» more  IROS 2009»
15 years 10 months ago
Learning locomotion over rough terrain using terrain templates
— We address the problem of foothold selection in robotic legged locomotion over very rough terrain. The difficulty of the problem we address here is comparable to that of human...
Mrinal Kalakrishnan, Jonas Buchli, Peter Pastor, S...
119
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SEKE
2004
Springer
15 years 8 months ago
Supporting the Requirements Prioritization Process. A Machine Learning approach
Requirements prioritization plays a key role in the requirements engineering process, in particular with respect to critical tasks such as requirements negotiation and software re...
Paolo Avesani, Cinzia Bazzanella, Anna Perini, Ang...