Sciweavers

324 search results - page 11 / 65
» Bounds for Functions of Dependent Risks
Sort
View
NIPS
2004
15 years 3 months ago
Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging
We study a method of optimal data-driven aggregation of classifiers in a convex combination and establish tight upper bounds on its excess risk with respect to a convex loss funct...
Vladimir Koltchinskii, Manel Martínez-Ram&o...
NAACL
2010
14 years 11 months ago
Softmax-Margin CRFs: Training Log-Linear Models with Cost Functions
We describe a method of incorporating taskspecific cost functions into standard conditional log-likelihood (CLL) training of linear structured prediction models. Recently introduc...
Kevin Gimpel, Noah A. Smith
COLT
2006
Springer
15 years 5 months ago
A Randomized Online Learning Algorithm for Better Variance Control
We propose a sequential randomized algorithm, which at each step concentrates on functions having both low risk and low variance with respect to the previous step prediction functi...
Jean-Yves Audibert
HPDC
2007
IEEE
15 years 8 months ago
A statistical approach to risk mitigation in computational markets
We study stochastic models to mitigate the risk of poor Quality-of-Service (QoS) in computational markets. Consumers who purchase services expect both price and performance guaran...
Thomas Sandholm, Kevin Lai
117
Voted
JMLR
2008
95views more  JMLR 2008»
15 years 1 months ago
Learning Similarity with Operator-valued Large-margin Classifiers
A method is introduced to learn and represent similarity with linear operators in kernel induced Hilbert spaces. Transferring error bounds for vector valued large-margin classifie...
Andreas Maurer