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» Learning Models for Predicting Recognition Performance
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113
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AR
2002
157views more  AR 2002»
15 years 2 months ago
Acquiring state from control dynamics to learn grasping policies for robot hands
Abstract--A prominent emerging theory of sensorimotor development in biological systems proposes that control knowledge is encoded in the dynamics of physical interaction with the ...
Roderic A. Grupen, Jefferson A. Coelho Jr.
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 3 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
141
Voted
ICML
2008
IEEE
16 years 3 months ago
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...
Ruslan Salakhutdinov, Andriy Mnih
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 3 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...
114
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EENERGY
2010
15 years 6 months ago
Towards energy-aware scheduling in data centers using machine learning
As energy-related costs have become a major economical factor for IT infrastructures and data-centers, companies and the research community are being challenged to find better an...
Josep Lluis Berral, Iñigo Goiri, Ramon Nou,...