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SDM
2009
SIAM
202views Data Mining» more  SDM 2009»
14 years 4 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
2011
IEEE
12 years 11 months ago
Robust Tracking Using Local Sparse Appearance Model and K-Selection
Online learned tracking is widely used for it’s adaptive ability to handle appearance changes. However, it introduces potential drifting problems due to the accumulation of erro...
Baiyang Liu, junzhou Huang, Casimir Kulikowski, Li...
ICCV
2009
IEEE
1318views Computer Vision» more  ICCV 2009»
15 years 19 days ago
Non-Local Sparse Models for Image Restoration
We propose in this paper to unify two different ap- proaches to image restoration: On the one hand, learning a basis set (dictionary) adapted to sparse signal descriptions has p...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
CIKM
2007
Springer
14 years 1 months ago
Generalizing from relevance feedback using named entity wildcards
Traditional adaptive filtering systems learn the user’s interests in a rather simple way – words from relevant documents are favored in the query model, while words from irre...
Abhimanyu Lad, Yiming Yang
AROBOTS
1999
87views more  AROBOTS 1999»
13 years 7 months ago
Dynamics of a Classical Conditioning Model
Abstract. Classical conditioning is a basic learning mechanism in animals and can be found in almost all organisms. If we want to construct robots with abilities matching those of ...
Christian Balkenius