This paper presents a search algorithm for finding functions that are highly correlated with an arbitrary set of data. The functions found by the search can be used to approximate...
In this paper, a novel genetically-inspired visual learning method is proposed. Given the training images, this general approach induces a sophisticated feature-based recognition s...
Abstract. We propose a purely implicit solution to the contextual assumption generation problem in assume-guarantee reasoning. Instead of improving the L∗ algorithm — a learnin...
Yu-Fang Chen, Edmund M. Clarke, Azadeh Farzan, Min...
We use a lexicographical preference order on the problem space to combine solution synthesis with conflict learning. Given two preferred solutions of two subproblems, we can either...
In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a a new probabilistic planning rule representation to compactly ...
Hanna M. Pasula, Luke S. Zettlemoyer, Leslie Pack ...