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ICML
2007
IEEE
15 years 10 months ago
Structural alignment based kernels for protein structure classification
Structural alignments are the most widely used tools for comparing proteins with low sequence similarity. The main contribution of this paper is to derive various kernels on prote...
Sourangshu Bhattacharya, Chiranjib Bhattacharyya, ...
COLT
2008
Springer
14 years 11 months ago
Injective Hilbert Space Embeddings of Probability Measures
A Hilbert space embedding for probability measures has recently been proposed, with applications including dimensionality reduction, homogeneity testing and independence testing. ...
Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fu...
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IJCV
2007
208views more  IJCV 2007»
14 years 9 months ago
Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes
We derive a family of kernels on dynamical systems by applying the Binet-Cauchy theorem to trajectories of states. Our derivation provides a unifying framework for all kernels on d...
S. V. N. Vishwanathan, Alexander J. Smola, Ren&eac...
SADM
2010
128views more  SADM 2010»
14 years 8 months ago
Online training on a budget of support vector machines using twin prototypes
: This paper proposes twin prototype support vector machine (TVM), a constant space and sublinear time support vector machine (SVM) algorithm for online learning. TVM achieves its ...
Zhuang Wang, Slobodan Vucetic
CVPR
2009
IEEE
16 years 4 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin