This paper addresses the problem of using appearance and motion models in classifying and tracking objects when detailed information of the object’s appearance is not available....
Deterministic dependency parsing has often been regarded as an efficient parsing algorithm while its parsing accuracy is a little lower than the best results reported by more comp...
Unifying first-order logic and probability is a long-standing goal of AI, and in recent years many representations combining aspects of the two have been proposed. However, infere...
Context-sensitive Multiple Task Learning, or csMTL, is presented as a method of inductive transfer that uses a single output neural network and additional contextual inputs for le...
Rule extraction is a technique aimed at transforming highly accurate opaque models like neural networks into comprehensible models without losing accuracy. G-REX is a rule extract...