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ACL
2006
13 years 11 months ago
Approximation Lasso Methods for Language Modeling
Lasso is a regularization method for parameter estimation in linear models. It optimizes the model parameters with respect to a loss function subject to model complexities. This p...
Jianfeng Gao, Hisami Suzuki, Bin Yu
FLAIRS
2006
13 years 11 months ago
Learning Personalized Query Modifications
The continuous development of the Internet has resulted in an exponential increase in the amount of available information. A popular way to access this information is by submittin...
Erika E. Torres-Verdín, Manfred Huber
IJCAI
2001
13 years 11 months ago
Complexity of Probabilistic Planning under Average Rewards
A general and expressive model of sequential decision making under uncertainty is provided by the Markov decision processes (MDPs) framework. Complex applications with very large ...
Jussi Rintanen
UAI
2001
13 years 11 months ago
A Bayesian Multiresolution Independence Test for Continuous Variables
In this paper we present a method of computing the posterior probability of conditional independence of two or more continuous variables from data, examined at several resolutions...
Dimitris Margaritis, Sebastian Thrun
UAI
2004
13 years 11 months ago
PAC-learning Bounded Tree-width Graphical Models
We show that the class of strongly connected graphical models with treewidth at most k can be properly efficiently PAC-learnt with respect to the Kullback-Leibler Divergence. Prev...
Mukund Narasimhan, Jeff A. Bilmes