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» Cosparse analysis modeling - uniqueness and algorithms
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ECRTS
2004
IEEE
15 years 7 months ago
An Event Stream Driven Approximation for the Analysis of Real-Time Systems
This paper presents a new approach to understand the event stream model. Additionally a new approximation algorithm for the feasibility test of the sporadic and the generalized mu...
Karsten Albers, Frank Slomka
186
Voted
STOC
2000
ACM
174views Algorithms» more  STOC 2000»
15 years 8 months ago
Noise-tolerant learning, the parity problem, and the statistical query model
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
Avrim Blum, Adam Kalai, Hal Wasserman
130
Voted
MA
2010
Springer
172views Communications» more  MA 2010»
15 years 2 months ago
On Monte Carlo methods for Bayesian multivariate regression models with heavy-tailed errors
We consider Bayesian analysis of data from multivariate linear regression models whose errors have a distribution that is a scale mixture of normals. Such models are used to analy...
Vivekananda Roy, James P. Hobert
151
Voted
PAMI
1998
103views more  PAMI 1998»
15 years 3 months ago
Synchronous Random Fields and Image Restoration
—We propose a general synchronous model of lattice random fields which could be used similarly to Gibbs distributions in a Bayesian framework for image analysis, leading to algor...
Laurent Younes
135
Voted
TACAS
1998
Springer
105views Algorithms» more  TACAS 1998»
15 years 8 months ago
Verification of Large State/Event Systems Using Compositionality and Dependency Analysis
A state/event model is a concurrent version of Mealy machines used for describing embedded reactive systems. This paper introduces a technique that uses compositionality and depend...
Jørn Lind-Nielsen, Henrik Reif Andersen, Ge...