Finding the sparsest solution for an under-determined linear system of equations D = s is of interest in many applications. This problem is known to be NP-hard. Recent work studie...
We describe a novel framework for the design and analysis of online learning algorithms based on the notion of duality in constrained optimization. We cast a sub-family of universa...
Abstract. We propose a SAT-based algorithm for incremental diagnosis of discrete-event systems. The monotonicity is ensured by a prediction window that uses the future observations...
Relational instance-based learning (RIBL) algorithms offer high prediction capabilities. However, they do not scale up well, specially in domains where there is a time bound for c...
—This paper describes efficient utilization of human time by two means: prioritization of human tasks and maximizing multirobot team size. We propose an efficient scheduling algo...