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...
Background: Information obtained from diverse data sources can be combined in a principled manner using various machine learning methods to increase the reliability and range of k...
Bolan Linghu, Evan S. Snitkin, Dustin T. Holloway,...
In this paper, we propose a distributed learning strategy in wireless sensor networks. Taking advantage of recent developments on kernel-based machine learning, we consider a new ...
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of re...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
Protein-protein interactions (PPI) play a key role in many biological systems. Over the past few years, an explosion in availability of functional biological data obtained from hi...