Sciweavers

18 search results - page 2 / 4
» Active covariance matrix adaptation for the (1 1)-CMA-ES
Sort
View
SDM
2009
SIAM
202views Data Mining» more  SDM 2009»
14 years 2 months ago
Proximity-Based Anomaly Detection Using Sparse Structure Learning.
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
Tsuyoshi Idé, Aurelie C. Lozano, Naoki Abe,...
CVPR
2007
IEEE
14 years 7 months ago
Active Visual Object Reconstruction using D-, E-, and T-Optimal Next Best Views
In visual 3-D reconstruction tasks with mobile cameras, one wishes to move the cameras so that they provide the views that lead to the best reconstruction result. When the camera ...
Stefan Wenhardt, Benjamin Deutsch, Elli Angelopoul...
GECCO
2010
Springer
237views Optimization» more  GECCO 2010»
13 years 9 months ago
Benchmarking the (1, 4)-CMA-ES with mirrored sampling and sequential selection on the noiseless BBOB-2010 testbed
The well-known Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a robust stochastic search algorithm for optimizing functions defined on a continuous search space RD ....
Anne Auger, Dimo Brockhoff, Nikolaus Hansen
GECCO
2010
Springer
187views Optimization» more  GECCO 2010»
13 years 9 months ago
Benchmarking the (1, 4)-CMA-ES with mirrored sampling and sequential selection on the noisy BBOB-2010 testbed
The Covariance-Matrix-Adaptation Evolution-Strategy (CMA-ES) is a robust stochastic search algorithm for optimizing functions defined on a continuous search space RD . Recently, ...
Anne Auger, Dimo Brockhoff, Nikolaus Hansen
TSP
2008
123views more  TSP 2008»
13 years 4 months ago
MIMO Radar Space-Time Adaptive Processing Using Prolate Spheroidal Wave Functions
In the traditional transmitting beamforming radar system, the transmitting antennas send coherent waveforms which form a highly focused beam. In the multiple-input multipleoutput (...
Chun-Yang Chen, Palghat P. Vaidyanathan