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NIPS
2008
15 years 7 months ago
An interior-point stochastic approximation method and an L1-regularized delta rule
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
Peter Carbonetto, Mark Schmidt, Nando de Freitas
ICML
2010
IEEE
15 years 7 months ago
Label Ranking Methods based on the Plackett-Luce Model
This paper introduces two new methods for label ranking based on a probabilistic model of ranking data, called the Plackett-Luce model. The idea of the first method is to use the ...
Weiwei Cheng, Krzysztof Dembczynski, Eyke Hül...
ML
1998
ACM
136views Machine Learning» more  ML 1998»
15 years 6 months ago
Co-Evolution in the Successful Learning of Backgammon Strategy
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
Jordan B. Pollack, Alan D. Blair
ICMCS
2009
IEEE
93views Multimedia» more  ICMCS 2009»
15 years 4 months ago
Learning based thumbnail cropping
Thumbnail cropping helps improve thumbnail readability by cropping images before shrinking them. In this paper we propose a learning based method for automatic thumbnail cropping....
Xin Li, Haibin Ling

Publication
154views
14 years 8 months ago
Preference elicitation and inverse reinforcement learning
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
Constantin Rothkopf, Christos Dimitrakakis