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» Approximation Methods for Supervised Learning
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MM
2004
ACM
167views Multimedia» more  MM 2004»
14 years 2 months ago
Learning an image manifold for retrieval
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
Xiaofei He, Wei-Ying Ma, HongJiang Zhang
STOC
1993
ACM
141views Algorithms» more  STOC 1993»
14 years 26 days ago
Bounds for the computational power and learning complexity of analog neural nets
Abstract. It is shown that high-order feedforward neural nets of constant depth with piecewisepolynomial activation functions and arbitrary real weights can be simulated for Boolea...
Wolfgang Maass
BMCBI
2010
154views more  BMCBI 2010»
13 years 9 months ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...
NAACL
2007
13 years 10 months ago
First-Order Probabilistic Models for Coreference Resolution
Traditional noun phrase coreference resolution systems represent features only of pairs of noun phrases. In this paper, we propose a machine learning method that enables features ...
Aron Culotta, Michael L. Wick, Andrew McCallum
NIPS
1997
13 years 10 months ago
Generalized Prioritized Sweeping
Prioritized sweeping is a model-based reinforcement learning method that attempts to focus an agent’s limited computational resources to achieve a good estimate of the value of ...
David Andre, Nir Friedman, Ronald Parr