We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
Practical cache replacement policies attempt to emulate optimal replacement by predicting the re-reference interval of a cache block. The commonly used LRU replacement policy alwa...
Aamer Jaleel, Kevin B. Theobald, Simon C. Steely J...
Background: A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of pro...
Background: Profile HMMs (hidden Markov models) provide effective methods for modeling the conserved regions of protein families. A limitation of the resulting domain models is th...
This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem b...