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KDD
2001
ACM
145views Data Mining» more  KDD 2001»
16 years 25 days ago
Proximal support vector machine classifiers
Given a dataset, each element of which labeled by one of k labels, we construct by a very fast algorithm, a k-category proximal support vector machine (PSVM) classifier. Proximal s...
Glenn Fung, Olvi L. Mangasarian
ML
2002
ACM
140views Machine Learning» more  ML 2002»
15 years 3 days ago
A Probabilistic Framework for SVM Regression and Error Bar Estimation
In this paper, we elaborate on the well-known relationship between Gaussian Processes (GP) and Support Vector Machines (SVM) under some convex assumptions for the loss functions. ...
Junbin Gao, Steve R. Gunn, Chris J. Harris, Martin...
94
Voted
NAACL
2010
14 years 10 months ago
An extractive supervised two-stage method for sentence compression
We present a new method that compresses sentences by removing words. In a first stage, it generates candidate compressions by removing branches from the source sentence's dep...
Dimitrios Galanis, Ion Androutsopoulos
88
Voted
ICIP
2006
IEEE
16 years 2 months ago
Estimating Illumination Chromaticity via Kernel Regression
We propose a simple nonparametric linear regression tool, known as kernel regression (KR), to estimate the illumination chromaticity. We design a Gaussian kernel whose bandwidth i...
Vivek Agarwal, Andrei V. Gribok, Andreas Koschan, ...
ESANN
2007
15 years 1 months ago
Model Selection for Kernel Probit Regression
Abstract. The convex optimisation problem involved in fitting a kernel probit regression (KPR) model can be solved efficiently via an iteratively re-weighted least-squares (IRWLS)...
Gavin C. Cawley