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» Margin Maximizing Loss Functions
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ICML
2004
IEEE
16 years 14 days ago
Links between perceptrons, MLPs and SVMs
We propose to study links between three important classification algorithms: Perceptrons, Multi-Layer Perceptrons (MLPs) and Support Vector Machines (SVMs). We first study ways to...
Ronan Collobert, Samy Bengio
TNN
2010
155views Management» more  TNN 2010»
14 years 6 months ago
Incorporating the loss function into discriminative clustering of structured outputs
Clustering using the Hilbert Schmidt independence criterion (CLUHSIC) is a recent clustering algorithm that maximizes the dependence between cluster labels and data observations ac...
Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. ...
ICPR
2006
IEEE
16 years 23 days ago
A Semi-supervised SVM for Manifold Learning
Many classification tasks benefit from integrating manifold learning and semi-supervised learning. By formulating the learning task in a semi-supervised manner, we propose a novel...
Zhili Wu, Chun-hung Li, Ji Zhu, Jian Huang
DATE
2008
IEEE
66views Hardware» more  DATE 2008»
15 years 6 months ago
Optimal Margin Computation for At-Speed Test
— In the face of increased process variations, at-speed manufacturing test is necessary to detect subtle delay defects. This procedure necessarily tests chips at a slightly highe...
Jinjun Xiong, Vladimir Zolotov, Chandu Visweswaria...
CORR
2010
Springer
134views Education» more  CORR 2010»
14 years 11 months ago
Large Margin Multiclass Gaussian Classification with Differential Privacy
As increasing amounts of sensitive personal information is aggregated into data repositories, it has become important to develop mechanisms for processing the data without revealin...
Manas A. Pathak, Bhiksha Raj