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PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
15 years 7 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
99
Voted
ICIP
1998
IEEE
15 years 4 months ago
Knowledge-based Segmentation of SAR Images
A new approach for the segmentation of still and video SAR images is described in this paper. A priori knowledge about the objects present in the image, e.g., target, shadow, and ...
Steven Haker, Guillermo Sapiro, Allen Tannenbaum
RECOMB
2003
Springer
16 years 1 months ago
Modeling dependencies in protein-DNA binding sites
The availability of whole genome sequences and high-throughput genomic assays opens the door for in silico analysis of transcription regulation. This includes methods for discover...
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kap...
89
Voted
ICML
2008
IEEE
16 years 1 months ago
Memory bounded inference in topic models
What type of algorithms and statistical techniques support learning from very large datasets over long stretches of time? We address this question through a memory bounded version...
Ryan Gomes, Max Welling, Pietro Perona
102
Voted
ICML
2006
IEEE
16 years 1 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh