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GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
15 years 7 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...
SIAMIS
2011
15 years 1 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
ICDE
2008
IEEE
117views Database» more  ICDE 2008»
16 years 1 months ago
Region Sampling: Continuous Adaptive Sampling on Sensor Networks
Abstract— Satisfying energy constraints while meeting performance requirements is a primary concern when a sensor network is being deployed. Many recent proposed techniques offer...
Song Lin, Benjamin Arai, Dimitrios Gunopulos, Gaut...
ALGOSENSORS
2007
Springer
16 years 26 days ago
Assigning Sensors to Missions with Demands
We introduce Semi-Matching with Demands (SMD), which models a certain problem in sensor networks of assigning individual sensors to sensing tasks. If there are multiple sensing tas...
Amotz Bar-Noy, Theodore Brown, Matthew P. Johnson,...
FOCS
2005
IEEE
16 years 9 days ago
Mechanism Design via Machine Learning
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of r...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...