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CORR
2012
Springer
214views Education» more  CORR 2012»
12 years 1 months ago
Stochastic Low-Rank Kernel Learning for Regression
We present a novel approach to learn a kernelbased regression function. It is based on the use of conical combinations of data-based parameterized kernels and on a new stochastic ...
Pierre Machart, Thomas Peel, Liva Ralaivola, Sandr...
TEC
2008
135views more  TEC 2008»
13 years 5 months ago
Quantum Genetic Optimization
Abstract--The complexity of the selection procedure of a genetic algorithm that requires reordering, if we restrict the class of the possible fitness functions to varying fitness f...
Andrea Malossini, Enrico Blanzieri, T. Calarco
17
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PAMI
2007
155views more  PAMI 2007»
13 years 5 months ago
Localization of Shapes Using Statistical Models and Stochastic Optimization
—In this paper, we present a new model for deformations of shapes. A pseudolikelihood is based on the statistical distribution of the gradient vector field of the gray level. The...
François Destrempes, Max Mignotte, Jean-Fra...
IOR
2011
220views more  IOR 2011»
13 years 18 days ago
Optimal Inventory Policies when Purchase Price and Demand Are Stochastic
In this paper we consider the problem of a firm that faces a stochastic (Poisson) demand and must replenish from a market in which prices fluctuate, such as a commodity market. ...
Peter Berling, Victor Martínez-de-Alb&eacut...