In standard online learning, the goal of the learner is to maintain an average loss that is "not too big" compared to the loss of the best-performing function in a fixed...
Remote visualization of an arbitrary 2-D planar "cut" from a large volumetric dataset with random access has both gained importance and posed significant challenges over...
This paper presents and validates methods to extend reuse distance analysis of application locality characteristics to shared-memory multicore platforms by accounting for invalidat...
Derek L. Schuff, Benjamin S. Parsons, Vijay S. Pai
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
The widespread use of ontologies to associate semantics with data has resulted in a growing interest in the problem of learning predictive models from data sources that use differe...