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MOC
2000
88views more  MOC 2000»
15 years 2 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
100
Voted
MOC
1998
136views more  MOC 1998»
15 years 2 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»
14 years 9 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
129
Voted
ICISP
2010
Springer
15 years 6 months 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
15 years 4 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