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...
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
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....
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 ...
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...