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» Learning for Optical Flow Using Stochastic Optimization
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NAACL
2010
13 years 6 months ago
Learning Dense Models of Query Similarity from User Click Logs
The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...
ITS
2004
Springer
155views Multimedia» more  ITS 2004»
14 years 2 months ago
Modeling the Development of Problem Solving Skills in Chemistry with a Web-Based Tutor
This research describes a probabilistic approach for developing predictive models of how students learn problem-solving skills in general qualitative chemistry. The goal is to use ...
Ron Stevens, Amy Soller, Melanie Cooper, Marcia Sp...
ML
1998
ACM
101views Machine Learning» more  ML 1998»
13 years 8 months ago
Elevator Group Control Using Multiple Reinforcement Learning Agents
Recent algorithmic and theoretical advances in reinforcement learning (RL) have attracted widespread interest. RL algorithmshave appeared that approximatedynamic programming on an ...
Robert H. Crites, Andrew G. Barto
JMLR
2012
11 years 11 months ago
Krylov Subspace Descent for Deep Learning
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
Oriol Vinyals, Daniel Povey
DAC
2003
ACM
14 years 10 months ago
A cost-driven lithographic correction methodology based on off-the-shelf sizing tools
As minimum feature sizes continue to shrink, patterned features have become significantly smaller than the wavelength of light used in optical lithography. As a result, the requir...
Puneet Gupta, Andrew B. Kahng, Dennis Sylvester, J...