Keyword

margin maximization

Description: In machine learning, margin maximization is an optimization principle that seeks decision boundaries with the greatest separation between classes.

Primary topic: Machine Learning and Algorithms (20%)

OpenAlex ID: keywords/margin-maximization

A training algorithm for optimal margin classifiers

1992 · Bernhard E. Boser, Isabelle M. Guyon, et al. · 11,998

Analysis of Representations for Domain Adaptation

2007 · Shai Ben-David, John Blitzer, et al. · The MIT Press eBooks · 2,017

Support Vector Machines: Theory and Applications

2005 · Wang, Lipo · Studies in fuzziness and soft computing · 1,506

Max-Margin Markov Networks

2003 · Ben Taskar, Carlos Guestrin, et al. · 1,204

A combined SVM and LDA approach for classification

2006 · Tao Xiong, V. Cherkassky · IEEE International Joint Conference on Neural Networks (IJCNN) · 984

Boosting Algorithms as Gradient Descent

1999 · Llew Mason, Jonathan Baxter, et al. · 773

Maximum Neighborhood Margin Discriminant Projection for Classification

2014 · Jianping Gou, Yongzhao Zhan, et al. · The Scientific World JOURNAL · 744

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Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning

2012 · Antonio Criminisi, Jamie Shotton, et al. · Foundations and Trends® in Computer Graphics and Vision · 677

Optimization Techniques for Semi-Supervised Support Vector Machines

2008 · Olivier Chapelle, Vikas Sindhwani, et al. · MPG.PuRe (Max Planck Society) · 404

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Manifold Regularized Discriminative Nonnegative Matrix Factorization With Fast Gradient Descent

2011 · Naiyang Guan, Dacheng Tao, et al. · IEEE Transactions on Image Processing · 318

Multispectral landuse classification using neural networks and support vector machines: one or the other, or both?

2007 · B. Dixon, N. Candade · International Journal of Remote Sensing · 307

Discriminant Locally Linear Embedding With High-Order Tensor Data

2008 · Xuelong Li, S. Lin, et al. · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · 303

Links between perceptrons, MLPs and SVMs

2004 · Ronan Collobert, Samy Bengio · 302

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Pebl:web page classification without negative examples

2004 · Hwanjo Yu, Jiawei Han, et al. · IEEE Transactions on Knowledge and Data Engineering · 258

Large-Margin Multi-ViewInformation Bottleneck

2014 · Chang Xu, Dacheng Tao, et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 257

Support Vector Machines

2009 · Armin Shmilovici · Springer eBooks · 252

Training Recurrent Networks by Evolino

2007 · Jürgen Schmidhuber, Daan Wierstra, et al. · Neural Computation · 248

Feature space interpretation of SVMs with indefinite kernels

2005 · B. Haasdonk · IEEE Transactions on Pattern Analysis and Machine Intelligence · 233

Boosting in the limit: maximizing the margin of learned ensembles

1998 · Adam J. Grove, Dale Schuurmans · 232

An Introduction to Support Vector Machines

2003 · Bernhard Schölkop · Elsevier eBooks · 228

Inter-class sparsity based discriminative least square regression

2018 · Jie Wen, Yong Xu, et al. · Neural Networks · 219

Decision Forests for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning

2011 · Antonio Criminisi, Ender Konukoglu, et al. · 204

Semi-superyised support vector machines for unlabeled data classification

2001 · Glenn Fung, O. L. Mangasarian · Optimization methods & software · 203

Support vector machines

2023 · Dirk Valkenborg, Axel-Jan Rousseau, et al. · American Journal of Orthodontics and Dentofacial Orthopedics · 198

Manifold elastic net: a unified framework for sparse dimension reduction

2010 · Tianyi Zhou, Dacheng Tao, et al. · Data Mining and Knowledge Discovery · 195

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Works count: 950

Citation count: 36,400