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CADE
2001
Springer
14 years 7 months ago
Context Trees
Context trees are a popular and effective tool for tasks such as compression, sequential prediction, and language modeling. We present an algebraic perspective of context trees for...
Harald Ganzinger, Robert Nieuwenhuis, Pilar Nivela
NIPS
2008
13 years 9 months ago
Theory of matching pursuit
We analyse matching pursuit for kernel principal components analysis (KPCA) by proving that the sparse subspace it produces is a sample compression scheme. We show that this bound...
Zakria Hussain, John Shawe-Taylor
SODA
2012
ACM
170views Algorithms» more  SODA 2012»
11 years 10 months ago
Compression via matroids: a randomized polynomial kernel for odd cycle transversal
The Odd Cycle Transversal problem (OCT) asks whether a given graph can be made bipartite by deleting at most k of its vertices. In a breakthrough result Reed, Smith, and Vetta (Op...
Stefan Kratsch, Magnus Wahlström
ICASSP
2011
IEEE
12 years 11 months ago
Using the kernel trick in compressive sensing: Accurate signal recovery from fewer measurements
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
Hanchao Qi, Shannon Hughes
ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
14 years 1 months ago
Fast On-line Kernel Learning for Trees
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...