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» A Practical Method for the Sparse Resultant
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PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
15 years 11 months ago
Sparse Kernel SVMs via Cutting-Plane Training
We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
Thorsten Joachims, Chun-Nam John Yu
152
Voted
ICPR
2008
IEEE
15 years 11 months ago
Text detection from scene images using sparse representation
A sparse representation based method is proposed for text detection from scene images. We start with edge information extracted using Canny operator and then group these edge poin...
Wumo Pan, Tien D. Bui, Ching Y. Suen
146
Voted
ESANN
2004
15 years 6 months ago
Sparse Bayesian kernel logistic regression
In this paper we present a simple hierarchical Bayesian treatment of the sparse kernel logistic regression (KLR) model based MacKay's evidence approximation. The model is re-p...
Gavin C. Cawley, Nicola L. C. Talbot
142
Voted
DIS
2010
Springer
15 years 2 months ago
Sparse Substring Pattern Set Discovery Using Linear Programming Boosting
In this paper, we consider finding a small set of substring patterns which classifies the given documents well. We formulate the problem as 1 norm soft margin optimization problem ...
Kazuaki Kashihara, Kohei Hatano, Hideo Bannai, Mas...
138
Voted
CORR
2011
Springer
200views Education» more  CORR 2011»
14 years 11 months ago
Sequential Analysis in High Dimensional Multiple Testing and Sparse Recovery
—This paper studies the problem of high-dimensional multiple testing and sparse recovery from the perspective of sequential analysis. In this setting, the probability of error is...
Matt Malloy, Robert Nowak