This paper addresses the problem of learning object models from egocentric video of household activities, using extremely weak supervision. For each activity sequence, we know onl...
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...