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» Approximation Methods for Supervised Learning
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MM
2004
ACM
167views Multimedia» more  MM 2004»
15 years 7 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»
15 years 6 months 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»
15 years 2 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
15 years 3 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
15 years 3 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