Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
This paper describes a complete system for reading typewritten lexicon words in noisy images - in this case museum index cards. The system is conceptually simple, and straightforw...
The Edinburgh Mouse Atlas aims to capture in-situ gene expression patterns in a common spatial framework. In this study, we construct a grammar to define spatial regions by combina...
As data of an unprecedented scale are becoming accessible, skyline queries have been actively studied lately, to retrieve “interesting” data objects that are not dominated by a...
We present a new algorithm for probabilistic planning with no observability. Our algorithm, called Probabilistic-FF, extends the heuristic forward-search machinery of Conformant-F...