We extend our recent work on relevant subtask learning, a new variant of multitask learning where the goal is to learn a good classifier for a task-of-interest with too few train...
Adaptation techniques based on importance weighting were shown effective for RankSVM and RankNet, viz., each training instance is assigned a target weight denoting its importance ...
We present a sound and complete calculus for causal relevance that uses Pearl's functional causal models as semantics. The calculus consists of axioms and rules of inference ...
This paper proposes an efficient relevance feedback based interactive model for keyword generation in sponsored search advertising. We formulate the ranking of relevant terms as a...
The University of Illinois at Urbana-Champaign (UIUC) participated in TREC 2007 Genomics Track. Our general goal of participation is to apply language modelbased approaches to the...