Abstract. Probabilistic timed automata are an extension of timed automata with discrete probability distributions. In previous work, a probabilistic notion of time divergence for p...
We present a novel algorithm to compute cache-efficient layouts of bounding volume hierarchies (BVHs) of polygonal models. Our approach does not make any assumptions about the cac...
When related learning tasks are naturally arranged in a hierarchy, an appealing approach for coping with scarcity of instances is that of transfer learning using a hierarchical Ba...
Gal Elidan, Benjamin Packer, Geremy Heitz, Daphne ...
Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can p...
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyv...
Our work deals with schema or ontology matching and is driven by the following statements: (1) Most of works only consider intensional description of schemas; (2) They mostly use s...