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ICML
2004
IEEE
14 years 9 months ago
Multiple kernel learning, conic duality, and the SMO algorithm
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
Francis R. Bach, Gert R. G. Lanckriet, Michael I. ...
MCS
2001
Springer
14 years 1 months ago
Genetic Programming for Improved Receiver Operating Characteristics
Genetic programming (GP) can automatically fuse given classifiers of diverse types to produce a combined classifier whose Receiver Operating Characteristics (ROC) are better than...
William B. Langdon, Bernard F. Buxton
AIPS
2004
13 years 10 months ago
Heuristic Refinements of Approximate Linear Programming for Factored Continuous-State Markov Decision Processes
Approximate linear programming (ALP) offers a promising framework for solving large factored Markov decision processes (MDPs) with both discrete and continuous states. Successful ...
Branislav Kveton, Milos Hauskrecht
ANOR
2006
69views more  ANOR 2006»
13 years 8 months ago
A splitting method for stochastic programs
This paper derives a new splitting-based decomposition algorithm for convex stochastic programs. It combines certain attractive features of the progressive hedging algorithm of Roc...
Teemu Pennanen, Markku Kallio
CASES
2009
ACM
13 years 6 months ago
Mapping stream programs onto heterogeneous multiprocessor systems
This paper presents a partitioning and allocation algorithm for an iterative stream compiler, targeting heterogeneous multiprocessors with constrained distributed memory and any c...
Paul M. Carpenter, Alex Ramírez, Eduard Ayg...