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ML
2010
ACM
181views Machine Learning» more  ML 2010»
15 years 3 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor
151
Voted
ICASSP
2010
IEEE
15 years 5 months ago
A kernel mean matching approach for environment mismatch compensation in speech recognition
The mismatch between training and test environmental conditions presents a challenge to speech recognition systems. In this paper, we investigate an approach for matching the dist...
Abhishek Kumar, John H. L. Hansen
ICDM
2003
IEEE
135views Data Mining» more  ICDM 2003»
15 years 10 months ago
An Algorithm for the Exact Computation of the Centroid of Higher Dimensional Polyhedra and its Application to Kernel Machines
The Support Vector Machine (SVM) solution corresponds to the centre of the largest sphere inscribed in version space. Alternative approaches like Bayesian Point Machines (BPM) and...
Frédéric Maire
CVPR
2001
IEEE
16 years 7 months ago
Adaptive Quasiconformal Kernel Metric for Image Retrieval
This paper presents a new approach to ranking relevant images for retrieval. Distance in the feature space associated with a kernel is used to rank relevant images. An adaptive qu...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai
DAGM
2011
Springer
14 years 5 months ago
Relaxed Exponential Kernels for Unsupervised Learning
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...