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ICML
2010
IEEE
8 years 11 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
UAI
2000
8 years 11 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
NIPS
2000
8 years 11 months ago
A Support Vector Method for Clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladi...
NIPS
2003
8 years 11 months ago
Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds
The decision functions constructed by support vector machines (SVM’s) usually depend only on a subset of the training set—the so-called support vectors. We derive asymptotical...
Ingo Steinwart
NIPS
2004
8 years 11 months ago
Face Detection - Efficient and Rank Deficient
This paper proposes a method for computing fast approximations to support vector decision functions in the field of object detection. In the present approach we are building on an...
Wolf Kienzle, Gökhan H. Bakir, Matthias O. Fr...
AAAI
2006
8 years 11 months ago
Closest Pairs Data Selection for Support Vector Machines
This paper presents data selection procedures for support vector machines (SVM). The purpose of data selection is to reduce the dataset by eliminating as many non support vectors ...
Chaofan Sun
NIPS
2007
8 years 11 months ago
A Randomized Algorithm for Large Scale Support Vector Learning
This paper investigates the application of randomized algorithms for large scale SVM learning. The key contribution of the paper is to show that, by using ideas random projections...
Krishnan Kumar, Chiru Bhattacharyya, Ramesh Hariha...
ESANN
2007
8 years 11 months ago
Kernel-based online machine learning and support vector reduction
We apply kernel-based machine learning methods to online learning situations, and look at the related requirement of reducing the complexity of the learnt classifier. Online meth...
Sumeet Agarwal, V. Vijaya Saradhi, Harish Karnick
KES
2000
Springer
9 years 1 months ago
Multi-view face detection using support vector machines and eigenspace modelling
An approach to multi-view face detection based on head pose estimation is presented in this paper. Support Vector Regression is employed to solve the problem of pose estimation. T...
Yongmin Li, Shaogang Gong, Jamie Sherrah, Heather ...
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