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ICDE
2006
IEEE
163views Database» more  ICDE 2006»
16 years 1 months ago
A Sampling-Based Approach to Optimizing Top-k Queries in Sensor Networks
Wireless sensor networks generate a vast amount of data. This data, however, must be sparingly extracted to conserve energy, usually the most precious resource in battery-powered ...
Adam Silberstein, Carla Schlatter Ellis, Jun Yang ...
CEC
2008
IEEE
15 years 6 months ago
A parallel surrogate-assisted multi-objective evolutionary algorithm for computationally expensive optimization problems
Abstract— This paper presents a new efficient multiobjective evolutionary algorithm for solving computationallyintensive optimization problems. To support a high degree of parall...
Anna Syberfeldt, Henrik Grimm, Amos Ng, Robert Ivo...
MANSCI
2008
122views more  MANSCI 2008»
14 years 11 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 ...
NIPS
2004
15 years 1 months ago
Optimal Information Decoding from Neuronal Populations with Specific Stimulus Selectivity
A typical neuron in visual cortex receives most inputs from other cortical neurons with a roughly similar stimulus preference. Does this arrangement of inputs allow efficient read...
Marcelo A. Montemurro, Stefano Panzeri
MIA
2010
170views more  MIA 2010»
14 years 6 months ago
Linear intensity-based image registration by Markov random fields and discrete optimization
We propose a framework for intensity-based registration of images by linear transformations, based on a discrete Markov Random Field (MRF) formulation. Here, the challenge arises ...
Darko Zikic, Ben Glocker, Oliver Kutter, Martin Gr...