Lack of labeled training examples is a common problem for many applications. In the same time, there is usually an abundance of labeled data from related tasks. But they have diff...
Xiaoxiao Shi, Qi Liu, Wei Fan, Qiang Yang, Philip ...
This paper proposes two variants of a simple but efficient algorithm for structure-preserving halftoning. Our algorithm extends Floyd-Steinberg error diffusion; the goal of our ex...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
One of the obstacles in automatic program proving is to obtain suitable loop invariants. The invariant of a loop is a weakened form of its postcondition (the loop's goal, als...
Abstract. Learning in the context of constraint solving is a technique by which previously unknown constraints are uncovered during search and used to speed up subsequent search. R...
Ian P. Gent, Christopher Jefferson, Lars Kotthoff,...