Abstract. The paper presents a partial order reduction method applicable to networks of timed automata. The advantage of the method is that it reduces both the number of explored c...
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
Local feature approaches to vision geometry and object recognition are based on selecting and matching sparse sets of visually salient image points, known as `keypoints' or `p...
This paper proposes a learning approach for the merging process in multilingual information retrieval (MLIR). To conduct the learning approach, we also present a large number of f...
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...