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ECRTS
2004
IEEE
15 years 10 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
STOC
2000
ACM
174views Algorithms» more  STOC 2000»
15 years 10 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
MA
2010
Springer
172views Communications» more  MA 2010»
15 years 4 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
PAMI
1998
103views more  PAMI 1998»
15 years 6 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
TACAS
1998
Springer
105views Algorithms» more  TACAS 1998»
15 years 10 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...