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ICML
2009
IEEE
16 years 7 months ago
Proximal regularization for online and batch learning
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
STOC
2004
ACM
126views Algorithms» more  STOC 2004»
16 years 7 months ago
Bypassing the embedding: algorithms for low dimensional metrics
The doubling dimension of a metric is the smallest k such that any ball of radius 2r can be covered using 2k balls of raThis concept for abstract metrics has been proposed as a na...
Kunal Talwar
EDOC
2009
IEEE
16 years 1 months ago
An End-to-End Approach for QoS-Aware Service Composition
Abstract—A simple and effective composition of software services into higher-level composite services is still a very challenging task. Especially in enterprise environments, Qua...
Florian Rosenberg, Predrag Celikovic, Anton Michlm...
IPPS
2009
IEEE
16 years 1 months ago
Scalability challenges for massively parallel AMR applications
PDE solvers using Adaptive Mesh Refinement on block structured grids are some of the most challenging applications to adapt to massively parallel computing environments. We descr...
Brian van Straalen, John Shalf, Terry J. Ligocki, ...
GECCO
2009
Springer
16 years 1 months ago
On the scalability of XCS(F)
Many successful applications have proven the potential of Learning Classifier Systems and the XCS classifier system in particular in datamining, reinforcement learning, and func...
Patrick O. Stalph, Martin V. Butz, David E. Goldbe...