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APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 10 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
JMLR
2008
159views more  JMLR 2008»
15 years 4 months ago
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to ...
Andreas Krause, Ajit Paul Singh, Carlos Guestrin
TIP
2010
113views more  TIP 2010»
14 years 11 months ago
Multiplicative Noise Removal Using Variable Splitting and Constrained Optimization
Multiplicative noise (also known as speckle noise) models are central to the study of coherent imaging systems, such as synthetic aperture radar and sonar, and ultrasound and laser...
José M. Bioucas-Dias, Mário A. T. Fi...
INFOCOM
2011
IEEE
14 years 8 months ago
Optimal control of epidemic evolution
—Epidemic models based on nonlinear differential equations have been extensively applied in a variety of systems as diverse as infectious outbreaks, marketing, diffusion of belie...
M. H. R. Khouzani, Saswati Sarkar, Eitan Altman
EWC
2010
91views more  EWC 2010»
15 years 3 months ago
Multiobjective global surrogate modeling, dealing with the 5-percent problem
When dealing with computationally expensive simulation codes or process measurement data, surrogate modeling methods are firmly established as facilitators for design space explor...
Dirk Gorissen, Ivo Couckuyt, Eric Laermans, Tom Dh...