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» An Anytime Algorithm for Decision Making under Uncertainty
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ICML
2000
IEEE
14 years 8 months ago
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...
Paul Komarek, Andrew W. Moore
IEEEPACT
2003
IEEE
14 years 25 days ago
Picking Statistically Valid and Early Simulation Points
Modern architecture research relies heavily on detailed pipeline simulation. Simulating the full execution of an industry standard benchmark can take weeks to months to complete. ...
Erez Perelman, Greg Hamerly, Brad Calder
ICCS
2003
Springer
14 years 23 days ago
Self-Adapting Numerical Software and Automatic Tuning of Heuristics
Self-Adapting Numerical Software (SANS) systems aim to bridge the knowledge gap that exists between the expertise of domain scientists, and the know-how that is needed to fulfill...
Jack Dongarra, Victor Eijkhout
NIPS
2007
13 years 9 months ago
Computing Robust Counter-Strategies
Adaptation to other initially unknown agents often requires computing an effective counter-strategy. In the Bayesian paradigm, one must find a good counterstrategy to the inferre...
Michael Johanson, Martin Zinkevich, Michael H. Bow...
COMCOM
2006
110views more  COMCOM 2006»
13 years 7 months ago
Localized routing with guaranteed delivery and a realistic physical layer in wireless sensor networks
Routing is the problem of sending a packet from a source node to a destination node in the network. Existing solutions for sensor networks assume a unit disk graph model, where me...
Milos Stojmenovic, Amiya Nayak