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ICML
2006
IEEE
16 years 5 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
ICCBR
2009
Springer
15 years 11 months ago
An Active Approach to Automatic Case Generation
Abstract. When learning by observing an expert, cases can be automatically generated in an inexpensive manner. However, since this is a passive method of learning the observer has ...
Michael W. Floyd, Babak Esfandiari
IPPS
2008
IEEE
15 years 10 months ago
Adaptive Locality-Effective Kernel Machine for protein phosphorylation site prediction
In this study, we propose a new machine learning model namely, Adaptive Locality-Effective Kernel Machine (Adaptive-LEKM) for protein phosphorylation site prediction. Adaptive-LEK...
Paul D. Yoo, Yung Shwen Ho, Bing Bing Zhou, Albert...
LREC
2008
125views Education» more  LREC 2008»
15 years 5 months ago
Adaptation of Relation Extraction Rules to New Domains
This paper presents various strategies for improving the extraction performance of less prominent relations with the help of the rules learned for similar relations, for which lar...
Feiyu Xu, Hans Uszkoreit, Hong Li, Niko Felger
CVPR
2009
IEEE
16 years 11 months ago
A Multi-View Probabilistic Model for 3D Object Classes
We propose a novel probabilistic framework for learning visual models of 3D object categories by combining appearance information and geometric constraints. Objects are represen...
Fei-Fei Li 0002, Hao Su, Min Sun, Silvio Savarese