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» Using model knowledge for learning inverse dynamics
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131
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CVPR
2008
IEEE
16 years 5 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
136
Voted
IDA
2005
Springer
15 years 9 months ago
Bayesian Networks Learning for Gene Expression Datasets
DNA arrays yield a global view of gene expression and can be used to build genetic networks models, in order to study relations between genes. Literature proposes Bayesian network ...
Giacomo Gamberoni, Evelina Lamma, Fabrizio Riguzzi...
111
Voted
ICALT
2005
IEEE
15 years 9 months ago
Building Repositories of Learning Objects in Specialized Domains: The Chasqui Approach
In this paper we describe the Chasqui approach to the construction of repositories of learning objects (LO) in specific knowledge areas. This approach is the result of our experie...
José Luis Sierra, Alfredo Fernández-...
124
Voted
EENERGY
2010
15 years 7 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,...
100
Voted
ECML
2006
Springer
15 years 7 months ago
Learning in One-Shot Strategic Form Games
Abstract. We propose a machine learning approach to action prediction in oneshot games. In contrast to the huge literature on learning in games where an agent's model is deduc...
Alon Altman, Avivit Bercovici-Boden, Moshe Tennenh...