Interactive clustering refers to situations in which a human labeler is willing to assist a learning algorithm in automatically clustering items. We present a related but somewhat...
Sumit Basu, Danyel Fisher, Steven M. Drucker, Hao ...
As computer architectures become increasingly complex, hand-tuning compiler heuristics becomes increasingly tedious and time consuming for compiler developers. This paper presents...
Matthew E. Taylor, Katherine E. Coons, Behnam Roba...
The precise specification of reward functions for Markov decision processes (MDPs) is often extremely difficult, motivating research into both reward elicitation and the robust so...
Goal-directed path planning is one of the basic and widely studied problems in the field of mobile robotics. Homotopy classes of trajectories, arising due to the presence of obsta...
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...