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MOC
2000
88views more  MOC 2000»
13 years 8 months ago
A posteriori error estimation for variational problems with uniformly convex functionals
The objective of this paper is to introduce a general scheme for deriving a posteriori error estimates by using duality theory of the calculus of variations. We consider variationa...
Sergey I. Repin
MOC
1998
136views more  MOC 1998»
13 years 8 months ago
Total variation diminishing Runge-Kutta schemes
In this paper we further explore a class of high order TVD (total variation diminishing) Runge-Kutta time discretization initialized in a paper by Shu and Osher, suitable for solvi...
Sigal Gottlieb, Chi-Wang Shu
IJON
2010
109views more  IJON 2010»
13 years 3 months ago
Variational inference for Student-t MLP models
This paper presents a novel methodology to infer parameters of probabilistic models whose output noise is a Student-t distribution. The method is an extension of earlier work for ...
Hang T. Nguyen, Ian T. Nabney
ICISP
2010
Springer
14 years 12 days ago
Total Variation Minimization with Separable Sensing Operator
Compressed Imaging is the theory that studies the problem of image recovery from an under-determined system of linear measurements. One of the most popular methods in this field i...
Serge L. Shishkin, Hongcheng Wang, Gregory S. Hage...
COLT
2008
Springer
13 years 10 months ago
Extracting Certainty from Uncertainty: Regret Bounded by Variation in Costs
Prediction from expert advice is a fundamental problem in machine learning. A major pillar of the field is the existence of learning algorithms whose average loss approaches that ...
Elad Hazan, Satyen Kale