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IJCAI
2001
13 years 9 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
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...
Ronen I. Brafman, Moshe Tennenholtz
CC
2006
Springer
124views System Software» more  CC 2006»
13 years 11 months ago
Hybrid Optimizations: Which Optimization Algorithm to Use?
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...
FORTE
2010
13 years 9 months ago
On Efficient Models for Model Checking Message-Passing Distributed Protocols
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...
Péter Bokor, Marco Serafini, Neeraj Suri
EUC
2006
Springer
13 years 11 months ago
Dynamic Repartitioning of Real-Time Schedule on a Multicore Processor for Energy Efficiency
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...
Euiseong Seo, Yongbon Koo, Joonwon Lee
ESWA
2008
152views more  ESWA 2008»
13 years 7 months ago
Collaborative recommender systems: Combining effectiveness and efficiency
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...
Panagiotis Symeonidis, Alexandros Nanopoulos, Apos...