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PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
14 years 2 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
ICS
2000
Tsinghua U.
13 years 11 months ago
Push vs. pull: data movement for linked data structures
As the performance gap between the CPU and main memory continues to grow, techniques to hide memory latency are essential to deliver a high performance computer system. Prefetchin...
Chia-Lin Yang, Alvin R. Lebeck
DAC
2003
ACM
14 years 8 months ago
Accurate timing analysis by modeling caches, speculation and their interaction
Schedulability analysis of real-time embedded systems requires worst case timing guarantees of embedded software performance. This involves not only language level program analysi...
Xianfeng Li, Tulika Mitra, Abhik Roychoudhury
TSE
1998
116views more  TSE 1998»
13 years 7 months ago
A Framework-Based Approach to the Development of Network-Aware Applications
— Modern networks provide a QoS (quality of service) model to go beyond best-effort services, but current QoS models are oriented towards low-level network parameters (e.g., band...
Jürg Bolliger, Thomas R. Gross
IPPS
2007
IEEE
14 years 1 months ago
Speedup using Flowpaths for a Finite Difference Solution of a 3D Parabolic PDE
Partial differential equations (PDEs) are used to model physical phenomena and then appropriate convergent numerical algorithms are employed to solve them and create computer simu...
Darrin M. Hanna, Anna M. Spagnuolo, Michael DuChen...