R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
We introduce a new class of compiler heuristics: hybrid optimizations. Hybrid optimizations choose dynamically at compile time which optimization algorithm to apply from a set of d...
John Cavazos, J. Eliot B. Moss, Michael F. P. O'Bo...
Abstract. The complexity of distributed algorithms, such as state machine replication, motivates the use of formal methods to assist correctness verification. The design of the for...
Multicore processors promise higher throughput at lower power consumption than single core processors. Thus in the near future they will be widely used in hard real-time systems as...
Recommender systems base their operation on past user ratings over a collection of items, for instance, books, CDs, etc. Collaborative filtering (CF) is a successful recommendatio...