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FTCS
1998
144views more  FTCS 1998»
15 years 8 months ago
Improving Software Robustness with Dependability Cases
Programs fail mainly for two reasons: logic errors in the code, and exception failures. Exception failures can account for up to 2/3 of system crashes [6], hence are worthy of ser...
Roy A. Maxion, Robert T. Olszewski
AIPS
2009
15 years 7 months ago
Computing Robust Plans in Continuous Domains
We define the robustness of a sequential plan as the probability that it will execute successfully despite uncertainty in the execution environment. We consider a rich notion of u...
Christian Fritz, Sheila A. McIlraith
DATE
2010
IEEE
154views Hardware» more  DATE 2010»
15 years 7 months ago
Computing robustness of FlexRay schedules to uncertainties in design parameters
Abstract--In the current environment of rapidly changing invehicle requirements and ever-increasing functional content for automotive EE systems, there are several sources of uncer...
Arkadeb Ghosal, Haibo Zeng, Marco Di Natale, Yakov...
CVPR
2010
IEEE
15 years 7 months ago
Robust RVM regression using sparse outlier model
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
MANSCI
2008
122views more  MANSCI 2008»
15 years 6 months ago
Incorporating Asymmetric Distributional Information in Robust Value-at-Risk Optimization
Value-at-Risk (VaR) is one of the most widely accepted risk measures in the financial and insurance industries, yet efficient optimization of VaR remains a very difficult problem....
Karthik Natarajan, Dessislava Pachamanova, Melvyn ...