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NIPS
2004
13 years 9 months ago
Maximum Margin Clustering
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
JCP
2008
104views more  JCP 2008»
13 years 7 months ago
Analysis and Improved Recognition of Protein Names Using Transductive SVM
We first analyzed protein names using various dictionaries and databases and found five problems with protein names; i.e., the treatment of special characters, the treatment of hom...
Masaki Murata, Tomohiro Mitsumori, Kouichi Doi
PR
2007
133views more  PR 2007»
13 years 7 months ago
Incorporating multiple SVMs for automatic image annotation
In this paper, a novel automatic image annotation system is proposed, which integrates two sets of support vector machines (SVMs), namely the multiple instance learning (MIL)-base...
Xiaojun Qi, Yutao Han
ICASSP
2011
IEEE
12 years 11 months ago
Compensation of extrinsic variability in speaker verification systems on simulated Skype and HF channel data
In this work we focus on speaker verification on channels of varying quality, namely Skype and high frequency (HF) radio. In our setup, we assume to have telephone recordings of ...
Korbinian Riedhammer, Tobias Bocklet, Elmar Nö...
NPL
2006
137views more  NPL 2006»
13 years 7 months ago
Minimal Structure of Self-Organizing HCMAC Neural Network Classifier
The authors previously proposed a self-organizing Hierarchical Cerebellar Model Articulation Controller (HCMAC) neural network containing a hierarchical GCMAC neural network and a ...
Chih-Ming Chen, Yung-Feng Lu, Chin-Ming Hong