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» Kernel Regression with Order Preferences
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AAAI
2007
13 years 7 months ago
Kernel Regression with Order Preferences
We propose a novel kernel regression algorithm which takes into account order preferences on unlabeled data. Such preferences have the form that point x1 has a larger target value...
Xiaojin Zhu, Andrew B. Goldberg
ICPR
2010
IEEE
13 years 2 months ago
Multiple Kernel Learning with High Order Kernels
Previous Multiple Kernel Learning approaches (MKL) employ different kernels by their linear combination. Though some improvements have been achieved over methods using single kerne...
Shuhui Wang, Shuqiang Jiang, Qingming Huang, Qi Ti...
GLOBECOM
2008
IEEE
13 years 11 months ago
Distributed Regression in Sensor Networks with a Reduced-Order Kernel Model
Abstract—Over the past few years, wireless sensor networks received tremendous attention for monitoring physical phenomena, such as the temperature field in a given region. Appl...
Paul Honeine, Mehdi Essoloh, Cédric Richard...
AAAI
2006
13 years 6 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
ICDM
2005
IEEE
134views Data Mining» more  ICDM 2005»
13 years 10 months ago
A Preference Model for Structured Supervised Learning Tasks
The preference model introduced in this paper gives a natural framework and a principled solution for a broad class of supervised learning problems with structured predictions, su...
Fabio Aiolli