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CORR
2010
Springer
105views Education» more  CORR 2010»
13 years 6 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
ICML
2009
IEEE
14 years 8 months ago
Learning structurally consistent undirected probabilistic graphical models
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
Sushmita Roy, Terran Lane, Margaret Werner-Washbur...
ICDM
2009
IEEE
211views Data Mining» more  ICDM 2009»
14 years 2 months ago
Discovering Organizational Structure in Dynamic Social Network
—Applying the concept of organizational structure to social network analysis may well represent the power of members and the scope of their power in a social network. In this pap...
Jiangtao Qiu, Zhangxi Lin, Changjie Tang, Shaojie ...
SAC
2006
ACM
14 years 1 months ago
Induction of compact decision trees for personalized recommendation
We propose a method for induction of compact optimal recommendation policies based on discovery of frequent itemsets in a purchase database, followed by the application of standar...
Daniel Nikovski, Veselin Kulev
ICCV
2011
IEEE
12 years 7 months ago
Decision Tree Fields
This paper introduces a new formulation for discrete image labeling tasks, the Decision Tree Field (DTF), that combines and generalizes random forests and conditional random fiel...
Sebastian Nowozin, Carsten Rother, Shai Bagon, Ban...