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ICML
2009
IEEE
14 years 8 months ago
The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning
The purpose of this paper is three-fold. First, we formalize and study a problem of learning probabilistic concepts in the recently proposed KWIK framework. We give details of an ...
Carlos Diuk, Lihong Li, Bethany R. Leffler
CVPR
2005
IEEE
14 years 9 months ago
Combining Object and Feature Dynamics in Probabilistic Tracking
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
Leonid Taycher, John W. Fisher III, Trevor Darrell
18
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ICML
2008
IEEE
14 years 8 months ago
The asymptotics of semi-supervised learning in discriminative probabilistic models
Semi-supervised learning aims at taking advantage of unlabeled data to improve the efficiency of supervised learning procedures. For discriminative models however, this is a chall...
François Yvon, Nataliya Sokolovska, Olivier...
KDD
2010
ACM
259views Data Mining» more  KDD 2010»
13 years 11 months ago
A probabilistic model for personalized tag prediction
Social tagging systems have become increasingly popular for sharing and organizing web resources. Tag recommendation is a common feature of social tagging systems. Social tagging ...
Dawei Yin, Zhenzhen Xue, Liangjie Hong, Brian D. D...
COLING
2008
13 years 8 months ago
An Integrated Probabilistic and Logic Approach to Encyclopedia Relation Extraction with Multiple Features
We propose a new integrated approach based on Markov logic networks (MLNs), an effective combination of probabilistic graphical models and firstorder logic for statistical relatio...
Xiaofeng Yu, Wai Lam