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» On Efficiency of Learning: A Framework and Justification
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ICMLA
2009
13 years 5 months ago
Learning Deep Neural Networks for High Dimensional Output Problems
State-of-the-art pattern recognition methods have difficulty dealing with problems where the dimension of the output space is large. In this article, we propose a new framework ba...
Benjamin Labbé, Romain Hérault, Cl&e...
JMLR
2000
134views more  JMLR 2000»
13 years 7 months ago
Learning with Mixtures of Trees
This paper describes the mixtures-of-trees model, a probabilistic model for discrete multidimensional domains. Mixtures-of-trees generalize the probabilistic trees of Chow and Liu...
Marina Meila, Michael I. Jordan
ICML
2008
IEEE
14 years 8 months ago
A rate-distortion one-class model and its applications to clustering
In one-class classification we seek a rule to find a coherent subset of instances similar to a few positive examples in a large pool of instances. The problem can be formulated an...
Koby Crammer, Partha Pratim Talukdar, Fernando Per...
AAAI
2004
13 years 9 months ago
An Instance-Based State Representation for Network Repair
We describe a formal framework for diagnosis and repair problems that shares elements of the well known partially observable MDP and cost-sensitive classification models. Our cost...
Michael L. Littman, Nishkam Ravi, Eitan Fenson, Ri...
JMLR
2006
79views more  JMLR 2006»
13 years 7 months ago
Estimation of Gradients and Coordinate Covariation in Classification
We introduce an algorithm that simultaneously estimates a classification function as well as its gradient in the supervised learning framework. The motivation for the algorithm is...
Sayan Mukherjee, Qiang Wu