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STOC
2004
ACM
150views Algorithms» more  STOC 2004»
14 years 8 months ago
Typical properties of winners and losers in discrete optimization
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
René Beier, Berthold Vöcking
GECCO
2005
Springer
189views Optimization» more  GECCO 2005»
14 years 1 months ago
Molecular programming: evolving genetic programs in a test tube
We present a molecular computing algorithm for evolving DNA-encoded genetic programs in a test tube. The use of synthetic DNA molecules combined with biochemical techniques for va...
Byoung-Tak Zhang, Ha-Young Jang
UAI
2004
13 years 9 months ago
Probabilistic Index Maps for Modeling Natural Signals
One of the major problems in modeling natural signals is that signals with very similar structure may locally have completely different measurements, e.g., images taken under diff...
Nebojsa Jojic, Yaron Caspi, Manuel Reyes-Gomez
SASO
2007
IEEE
14 years 2 months ago
Novel Mathematics-Inspired Algorithms for Self-Adaptive Peer-to-Peer Computing
This paper describes, and evaluates benefits of, a design methodology to translate certain mathematical models into the design of novel, self-adaptive, peer-to-peer (p2p) distrib...
Steven Y. Ko, Indranil Gupta, Yookyung Jo
GECCO
2005
Springer
186views Optimization» more  GECCO 2005»
14 years 1 months ago
Subproblem optimization by gene correlation with singular value decomposition
Several ways of using singular value decomposition (SVD), a linear algebra technique typically used for information retrieval, to decompose problems into subproblems are investiga...
Jacob G. Martin