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NIPS
2004
13 years 8 months ago
Binet-Cauchy Kernels
We propose a family of kernels based on the Binet-Cauchy theorem and its extension to Fredholm operators. This includes as special cases all currently known kernels derived from t...
S. V. N. Vishwanathan, Alex J. Smola
CIBCB
2005
IEEE
14 years 1 months ago
The Homology Kernel: A Biologically Motivated Sequence Embedding into Euclidean Space
— Part of the challenge of modeling protein sequences is their discrete nature. Many of the most powerful statistical and learning techniques are applicable to points in a Euclid...
Eleazar Eskin, Sagi Snir
EMNLP
2006
13 years 8 months ago
Short Text Authorship Attribution via Sequence Kernels, Markov Chains and Author Unmasking: An Investigation
We present an investigation of recently proposed character and word sequence kernels for the task of authorship attribution based on relatively short texts. Performance is compare...
Conrad Sanderson, Simon Günter
IJCAI
2007
13 years 8 months ago
Parametric Kernels for Sequence Data Analysis
A key challenge in applying kernel-based methods for discriminative learning is to identify a suitable kernel given a problem domain. Many methods instead transform the input data...
Young-In Shin, Donald S. Fussell
CVPR
2007
IEEE
14 years 9 months ago
Recognizing Human Activities from Silhouettes: Motion Subspace and Factorial Discriminative Graphical Model
We describe a probabilistic framework for recognizing human activities in monocular video based on simple silhouette observations in this paper. The methodology combines kernel pr...
Liang Wang, David Suter