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» Kernel Methods for Pattern Analysis
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ICPR
2004
IEEE
14 years 8 months ago
Optimally Regularised Kernel Fisher Discriminant Analysis
Mika et al. [3] introduce a non-linear formulation of Fisher's linear discriminant, based the now familiar "kernel trick", demonstrating state-of-the-art performanc...
Gavin C. Cawley, Kamel Saadi, Nicola L. C. Talbot
ESANN
2004
13 years 9 months ago
Neural methods for non-standard data
Standard pattern recognition provides effective and noise-tolerant tools for machine learning tasks; however, most approaches only deal with real vectors of a finite and fixed dime...
Barbara Hammer, Brijnesh J. Jain
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 19 days ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
CIKM
2008
Springer
13 years 9 months ago
Kernel methods, syntax and semantics for relational text categorization
Previous work on Natural Language Processing for Information Retrieval has shown the inadequateness of semantic and syntactic structures for both document retrieval and categoriza...
Alessandro Moschitti
ICPR
2006
IEEE
14 years 8 months ago
Weakly Supervised Learning on Pre-image Problem in Kernel Methods
This paper presents a novel alternative approach, namely weakly supervised learning (WSL), to learn the pre-image of a feature vector in the feature space induced by a kernel. It ...
Weishi Zheng, Jian-Huang Lai, Pong Chi Yuen