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APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 3 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
COR
2007
106views more  COR 2007»
14 years 9 months ago
On a stochastic sequencing and scheduling problem
We present a framework for solving multistage pure 0–1 programs for a widely used sequencing and scheduling problem with uncertainty in the objective function coefficients, the...
Antonio Alonso-Ayuso, Laureano F. Escudero, M. Ter...
ICIP
2007
IEEE
15 years 11 months ago
Color Image Superresolution Based on a Stochastic Combinational Classification-Regression Algorithm
Abstract - The proposed algorithm in this work provides superresolution for color images by using a learning based technique that utilizes both generative and discriminant approach...
Karl S. Ni, Truong Q. Nguyen
BMCBI
2006
179views more  BMCBI 2006»
14 years 10 months ago
Multiscale Hy3S: Hybrid stochastic simulation for supercomputers
Background: Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuation...
Howard Salis, Vassilios Sotiropoulos, Yiannis N. K...
IFIP
2000
Springer
15 years 1 months ago
Test Case Design for the Validation of Component-Based Embedded Systems
The validation of functional and real-time requirements of control software for embedded systems is a difficult task. It usually needs the electronic control unit (ECU) and the co...
W. Fleisch