We consider the problem of learning mixtures of product distributions over discrete domains in the distribution learning framework introduced by Kearns et al. [18]. We give a poly...
There has been much interest in testing from finite state machines (FSMs) as a result of their suitability for modelling or specifying state-based systems. Where there are multip...
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
This paper develops new algorithms for coalition formation within multi-sensor networks tasked with performing widearea surveillance. Specifically, we cast this application as an ...
Viet Dung Dang, Rajdeep K. Dash, Alex Rogers, Nich...
In computational biology, gene order data is often modelled as signed permutations. A classical problem in genome comparison is to detect conserved segments in a permutation, that ...