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SDM
2012
SIAM
322views Data Mining» more  SDM 2012»
13 years 9 months ago
Adaptive Multi-task Sparse Learning with an Application to fMRI Study
In this paper, we consider the multi-task sparse learning problem under the assumption that the dimensionality diverges with the sample size. The traditional l1/l2 multi-task lass...
Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbo...
IJCNN
2006
IEEE
16 years 18 days ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
ECAI
2008
Springer
15 years 8 months ago
Heuristics for Dynamically Adapting Propagation
Building adaptive constraint solvers is a major challenge in constraint programming. An important line of research towards this goal is concerned with ways to dynamically adapt th...
Kostas Stergiou

Publication
468views
15 years 2 months ago
Visual object tracking via sample-based Adaptive Sparse Representation (AdaSR)
When appearance variation of object and its background, partial occlusion or deterioration in object images occurs, most existing visual tracking methods tend to fail in tracking ...
Zhenjun Han, Jianbin Jiao, Baochang Zhang, Qixiang...
ICDE
2008
IEEE
190views Database» more  ICDE 2008»
16 years 8 months ago
Adaptive Segmentation for Scientific Databases
In this paper we explore database segmentation in the context of a column-store DBMS targeted at a scientific database. We present a novel hardware- and scheme-oblivious segmentati...
Milena Ivanova, Martin L. Kersten, Niels Nes