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IJCAI
2007
15 years 4 months ago
Utile Distinctions for Relational Reinforcement Learning
We introduce an approach to autonomously creating state space abstractions for an online reinforcement learning agent using a relational representation. Our approach uses a tree-b...
William Dabney, Amy McGovern
138
Voted
NIPS
2008
15 years 4 months ago
Learning Bounded Treewidth Bayesian Networks
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
Gal Elidan, Stephen Gould
ACL
2001
15 years 4 months ago
Detecting Problematic Turns in Human-Machine Interactions: Rule-induction Versus Memory-based Learning Approaches
We address the issue of on-line detection of communication problems in spoken dialogue systems. The usefulness is investigated of the sequence of system question types and the wor...
Antal van den Bosch, Emiel Krahmer, Marc Swerts
ICML
2010
IEEE
15 years 4 months ago
Online Learning for Group Lasso
We develop a novel online learning algorithm for the group lasso in order to efficiently find the important explanatory factors in a grouped manner. Different from traditional bat...
Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Ly...
162
Voted
JMLR
2006
186views more  JMLR 2006»
15 years 3 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani