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PARA
2004
Springer
13 years 11 months ago
New Algorithms for Statistical Analysis of Interval Data
It is known that in general, statistical analysis of interval data is an NP-hard problem: even computing the variance of interval data is, in general, NP-hard. Until now, only one ...
Gang Xiang, Scott A. Starks, Vladik Kreinovich, Lu...
SAC
2006
ACM
13 years 11 months ago
Interval-based robust statistical techniques for non-negative convex functions, with application to timing analysis of computer
: In chip design, one of the main objectives is to decrease its clock cycle; however, the existing approaches to timing analysis under uncertainty are based on fundamentally restri...
Michael Orshansky, Wei-Shen Wang, Martine Ceberio,...
RC
2002
72views more  RC 2002»
13 years 5 months ago
Symbolic Preconditioning with Taylor Models: Some Examples
Deterministic global optimization with interval analysis involves - using interval enclosures for ranges of the constraints, objective, and gradient to reject infeasible regions, r...
R. Baker Kearfott, G. William Walster
TIM
2010
144views Education» more  TIM 2010»
13 years 15 days ago
Extending Polynomial Chaos to Include Interval Analysis
Polynomial chaos theory (PCT) has been proven to be an efficient and effective way to represent and propagate uncertainty through system models and algorithms in general. In partic...
Antonello Monti, Ferdinanda Ponci, Marco Valtorta
COLT
2005
Springer
13 years 11 months ago
Localized Upper and Lower Bounds for Some Estimation Problems
Abstract. We derive upper and lower bounds for some statistical estimation problems. The upper bounds are established for the Gibbs algorithm. The lower bounds, applicable for all ...
Tong Zhang