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» Metric and Kernel Learning Using a Linear Transformation
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NIPS
2008
15 years 3 months ago
Scalable Algorithms for String Kernels with Inexact Matching
We present a new family of linear time algorithms based on sufficient statistics for string comparison with mismatches under the string kernels framework. Our algorithms improve t...
Pavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic
118
Voted
PRL
2008
161views more  PRL 2008»
15 years 1 months ago
Automatic kernel clustering with a Multi-Elitist Particle Swarm Optimization Algorithm
This article introduces a scheme for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring groups in the data. T...
Swagatam Das, Ajith Abraham, Amit Konar
ICMCS
2007
IEEE
214views Multimedia» more  ICMCS 2007»
15 years 8 months ago
Exploring Discriminative Learning for Text-Independent Speaker Recognition
Speaker verification is a technology of verifying the claimed identity of a speaker based on the speech signal from the speaker (voice print). To learn the score of similarity be...
Ming Liu, Zhengyou Zhang, Mark Hasegawa-Johnson, T...
148
Voted
HUMO
2007
Springer
15 years 8 months ago
Multi-activity Tracking in LLE Body Pose Space
We present a method to simultaneously estimate 3d body pose and action categories from monocular video sequences. Our approach learns a lowdimensional embedding of the pose manifol...
Tobias Jaeggli, Esther Koller-Meier, Luc J. Van Go...
104
Voted
IJCAI
2007
15 years 3 months ago
Improving Embeddings by Flexible Exploitation of Side Information
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
Ali Ghodsi, Dana F. Wilkinson, Finnegan Southey