Recently, a number of frameworks were proposed to extend interface theory to the domains of single-processor and distributed real-time systems. This paper unifies some of these ap...
Lothar Thiele, Ernesto Wandeler, Nikolay Stoimenov
This paper investigates the impact of subspace based techniques for acoustic modeling in automatic speech recognition (ASR). There are many well known approaches to subspace based...
We present a technique to adapt the domain of local features through the matching process to augment their discriminative power. We start with local affine features selected and n...
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
This paper describes a new approach for solving disjunctive temporal problems such as the open shop and job shop scheduling domains. Much previous research in systematic search app...