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NIPS
1998
14 years 11 months ago
Dynamically Adapting Kernels in Support Vector Machines
The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...
Nello Cristianini, Colin Campbell, John Shawe-Tayl...
ECML
2006
Springer
15 years 1 months ago
The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces
Minimum volume covering ellipsoid estimation is important in areas such as systems identification, control, video tracking, sensor management, and novelty detection. It is well kno...
Alexander N. Dolia, Tijl De Bie, Christopher J. Ha...
AAAI
2006
14 years 11 months ago
Unsupervised Order-Preserving Regression Kernel for Sequence Analysis
In this work, a generalized method for learning from sequence of unlabelled data points based on unsupervised order-preserving regression is proposed. Sequence learning is a funda...
Young-In Shin
ICONIP
2004
14 years 11 months ago
Semi-supervised Kernel-Based Fuzzy C-Means
This paper presents a semi-supervised kernel-based fuzzy c-means algorithm called S2KFCM by introducing semi-supervised learning technique and the kernel method simultaneously into...
Daoqiang Zhang, Keren Tan, Songcan Chen
KDD
2005
ACM
143views Data Mining» more  KDD 2005»
15 years 10 months ago
SVM selective sampling for ranking with application to data retrieval
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Hwanjo Yu