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COLT
1993
Springer
15 years 7 months ago
Learning Binary Relations Using Weighted Majority Voting
In this paper we demonstrate how weighted majority voting with multiplicative weight updating can be applied to obtain robust algorithms for learning binary relations. We first pre...
Sally A. Goldman, Manfred K. Warmuth
135
Voted
GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
15 years 7 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
ML
2006
ACM
142views Machine Learning» more  ML 2006»
15 years 3 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
193
Voted
VLDB
2007
ACM
295views Database» more  VLDB 2007»
15 years 9 months ago
From Data Privacy to Location Privacy: Models and Algorithms
This tutorial presents the definition, the models and the techniques of location privacy from the data privacy perspective. By reviewing and revising the state of art research in ...
Ling Liu
MICCAI
2009
Springer
16 years 4 months ago
MKL for Robust Multi-modality AD Classification
We study the problem of classifying mild Alzheimer's disease (AD) subjects from healthy individuals (controls) using multi-modal image data, to facilitate early identification...
Chris Hinrichs, Vikas Singh, Guofan Xu, Sterlin...