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» Optimization of Convex Risk Functions
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ICASSP
2011
IEEE
13 years 2 months ago
Stochastic optimization based on the Laplace transform order with applications to precoder designs
Stochastic optimization arising from precoding in a multi-antenna fading channel with channel mean feedback to maximize data rates is important but challenging. The use of relayin...
Minhua Ding, Keith Q. T. Zhang
ANOR
2002
47views more  ANOR 2002»
13 years 10 months ago
Nonparametric Adverse Selection Problems
This article is devoted to adverse selection problems in which individual private information is a whole utility function and cannot be reduced to some finite-dimensional parameter...
Guillaume Carlier
NIPS
2008
13 years 11 months ago
Mind the Duality Gap: Logarithmic regret algorithms for online optimization
We describe a primal-dual framework for the design and analysis of online strongly convex optimization algorithms. Our framework yields the tightest known logarithmic regret bound...
Shai Shalev-Shwartz, Sham M. Kakade
RSKT
2009
Springer
14 years 4 months ago
Learning Optimal Parameters in Decision-Theoretic Rough Sets
A game-theoretic approach for learning optimal parameter values for probabilistic rough set regions is presented. The parameters can be used to define approximation regions in a p...
Joseph P. Herbert, Jingtao Yao
IVC
2007
114views more  IVC 2007»
13 years 10 months ago
Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views
We introduce a convex relaxation approach for the quadratic assignment problem to the field of computer vision. Due to convexity, a favourable property of this approach is the ab...
Christian Schellewald, Stefan Roth, Christoph Schn...