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WSC
2001
13 years 8 months ago
On improving the performance of simulation-based algorithms for average reward processes with application to network pricing
We address performance issues associated with simulationbased algorithms for optimizing Markov reward processes. Specifically, we are concerned with algorithms that exploit the re...
Enrique Campos-Náñez, Stephen D. Pat...
NECO
2007
150views more  NECO 2007»
13 years 7 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
WOSP
2004
ACM
14 years 25 days ago
Using locality of reference to improve performance of peer-to-peer applications
Peer-to-peer, or simply P2P, systems have recently emerged as a popular paradigm for building distributed applications. One key aspect of the P2P system design is the mechanism us...
Marcelo Werneck Barbosa, Melissa Morgado Costa, Ju...
ICCD
2007
IEEE
183views Hardware» more  ICCD 2007»
14 years 4 months ago
Constraint satisfaction in incremental placement with application to performance optimization under power constraints
We present new techniques for explicit constraint satisfaction in the incremental placement process. Our algorithm employs a Lagrangian Relaxation (LR) type approach in the analyt...
Huan Ren, Shantanu Dutt
CISIS
2011
IEEE
12 years 7 months ago
Improving Scheduling Techniques in Heterogeneous Systems with Dynamic, On-Line Optimisations
—Computational performance increasingly depends on parallelism, and many systems rely on heterogeneous resources such as GPUs and FPGAs to accelerate computationally intensive ap...
Marcin Bogdanski, Peter R. Lewis, Tobias Becker, X...