This paper is concerned with information theoretic "metrics" for comparing two dynamical systems. Following the recent work of Tryphon Georgiou [1], we outline a predicti...
Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...
We introduce a network-based problem detection framework for distributed systems, which includes a data-mining method for discovering dynamic dependencies among distributed servic...
— Vehicle following can be achieved by minimizing the relative information (Kullback-Leibler or K-L distance), between the estimated poses of leader and follower vehicles by form...
Teck Chew Ng, Martin David Adams, Javier Ibanez Gu...
Abstract Most ranking algorithms are based on the optimization of some loss functions, such as the pairwise loss. However, these loss functions are often different from the criter...