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» Comparing the Performance of Database Selection Algorithms
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ICASSP
2009
IEEE
16 years 1 months ago
RLS-weighted Lasso for adaptive estimation of sparse signals
The batch least-absolute shrinkage and selection operator (Lasso) has well-documented merits for estimating sparse signals of interest emerging in various applications, where obse...
Daniele Angelosante, Georgios B. Giannakis
CVPR
2012
IEEE
13 years 8 months ago
Changedetection.net: A new change detection benchmark dataset
Change detection is one of the most commonly encountered low-level tasks in computer vision and video processing. A plethora of algorithms have been developed to date, yet no wide...
Nil Goyette, Pierre-Marc Jodoin, Fatih Porikli, Ja...
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 6 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
ICDIM
2008
IEEE
16 years 21 days ago
Dynamic detection and administration of materialized views based on the Query Graph Model
Database Management Systems (DBMS) are complex software systems which are used in an increasing number of applications. To obtain the best performance for business relevant applic...
Andreas Lübcke, Ingolf Geist, Ronny Bubke
HVEI
2010
15 years 4 months ago
No-reference image quality assessment based on localized gradient statistics: application to JPEG and JPEG2000
This paper presents a novel system that employs an adaptive neural network for the no-reference assessment of perceived quality of JPEG/JPEG2000 coded images. The adaptive neural ...
Hantao Liu, Judith Redi, Hani Alers, Rodolfo Zunin...