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ESANN
2001
15 years 8 months ago
Learning fault-tolerance in Radial Basis Function Networks
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
Xavier Parra, Andreu Català
WSC
2001
15 years 8 months ago
Monte Carlo simulation approach to stochastic programming
Various stochastic programmingproblemscan be formulated as problems of optimization of an expected value function. Quite often the corresponding expectation function cannot be com...
Alexander Shapiro
NIPS
2003
15 years 8 months ago
Laplace Propagation
We present a novel method for approximate inference in Bayesian models and regularized risk functionals. It is based on the propagation of mean and variance derived from the Lapla...
Alexander J. Smola, Vishy Vishwanathan, Eleazar Es...
CORR
2010
Springer
100views Education» more  CORR 2010»
15 years 6 months ago
Convex Relaxations for Subset Selection
We use convex relaxation techniques to produce lower bounds on the optimal value of subset selection problems and generate good approximate solutions. We then explicitly bound the...
Francis Bach, Selin Damla Ahipasaoglu, Alexandre d...
ECCC
2006
75views more  ECCC 2006»
15 years 6 months ago
Note on MAX 2SAT
In this note we present an approximation algorithm for MAX 2SAT that given a (1 - ) satisfiable instance finds an assignment of variables satisfying a 1 - O( ) fraction of all co...
Moses Charikar, Konstantin Makarychev, Yury Makary...