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AI
1998
Springer
14 years 9 months ago
Model-Based Average Reward Reinforcement Learning
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
Prasad Tadepalli, DoKyeong Ok
SIGSOFT
2006
ACM
15 years 10 months ago
Dynamic slicing long running programs through execution fast forwarding
Fixing runtime bugs in long running programs using trace based analyses such as dynamic slicing was believed to be prohibitively expensive. In this paper, we present a novel execu...
Xiangyu Zhang, Sriraman Tallam, Rajiv Gupta
ADHOCNOW
2006
Springer
15 years 3 months ago
File System Support for Adjustable Resolution Applications in Sensor Networks
Flash memory is often the technology of choice for sensor networks because of its cost-effectiveness and attractive energy properties. In storage-constrained sensor network applica...
Vikram P. Munishwar, Sameer Tilak, Nael B. Abu-Gha...
EUROCRYPT
2005
Springer
15 years 3 months ago
Floating-Point LLL Revisited
The Lenstra-Lenstra-Lov´asz lattice basis reduction algorithm (LLL or L3 ) is a very popular tool in public-key cryptanalysis and in many other fields. Given an integer d-dimensi...
Phong Q. Nguyen, Damien Stehlé
ISSTA
2004
ACM
15 years 3 months ago
An optimizing compiler for batches of temporal logic formulas
Model checking based on validating temporal logic formulas has proven practical and effective for numerous software engineering applications. As systems based on this approach ha...
James Ezick