Support Vector Machines

Also known as SVM

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Overview

Support vector machines (SVMs) find decision boundaries that separate classes with a wide margin; kernels such as the Gaussian RBF and polynomial kernel extend them to nonlinear patterns. Related methods include support vector regression for continuous outcomes and one-class SVMs for anomaly detection, while robust losses, sparsity penalties, and twin or proximal formulations address noise and feature selection. Research also develops faster training and model selection through optimization methods, GPU computation, and low-rank approximations such as Nyström, and tests SVMs in settings from medical imaging to remote sensing. A central tension is that SVMs remain strong on many structured and tabular tasks, but performance depends heavily on kernel and preprocessing choices, while scalability, high-dimensional generalization, and reliable interpretation remain challenges.

Latest papers

CardsList

42 papers8 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

  1. Geodesic-SVDD Latent Mixup for One-Shot Distributed Tabular Learning

    Oct 24, 2026Andrea Moleri, Christian Internò, Markus Olhofer +2Federated LearningTabular ML

    Honda Research Institute Europe · University of Milan-Bicocca · Bielefeld University

  2. GBTSVR: Twin Support Vector Regression via Granular Ball Computing

    Oct 14, 2026A. Quadir, M. TanveerRobust RegressionSupport Vector Machines

    Department of Mathematics, Indian Institute of Technology Indore, Simrol, Indore, 453552, Madhya Pradesh, India

  3. Guarded Block Transfers for Polytope Distance: Linear Convergence with Explicit Constants and Gap-Certified Screening for SVM Training

    Oct 11, 2026Mayank GuptaSupport Vector Machines

    Independent Researcher

  4. Revisited Support Vector Machines: A Unified Joint Optimization Framework with Nyström Approximation for Scalable Adaptive Learning

    Oct 11, 2026Nassou Gongon Benjamin, Noulapeu Ngaffo, Patrick Njionou SadjangNyström MethodSupport Vector Machines

    Laboratory of Data Science and Artificial Intelligence (LSDIA), National Higher Polytechnic School of Douala (ENSPD), University of Douala, Cameroon · Department of Computer Sciences, National Higher Polytechnic School of Douala (ENSPD), University of Douala, Cameroon · Department of Basic Scientific Education, National Higher Polytechnic School of Douala (ENSPD), University of Douala, Cameroon

  5. Second-order optimization of variable projection SVM models and road abnormality detection

    Oct 7, 2026Andrea Angino, Matthias Voigt, Rolf Krause +1Second-Order OptimizationSupport Vector Machines

    Faculty of Mathematics and Computer Science, UniDistance Suisse, Brig, Switzerland · CEMSE Division, KAUST, Thuwal, Saudi Arabia · Eötvös Loránd University, Faculty of Informatics, Department of Numerical Analysis

  6. High-Dimensional Statistical Inference for Sparse Support Vector Machines

    Oct 6, 2026Peng Zeng, Hanwen HuangSupport Vector MachinesFeature Selection

    Department of Mathematics and Statistics Auburn University, Auburn, AL 36849 · Department of Biostatistics, Data Science and Epidemiology Medical College of Georgia, Augusta University, Augusta, GA, 30912

  7. Asymptotic Properties of Support Vector Machines in High-Dimension, Low-Sample-Size Settings under a Spiked Model

    Sep 30, 2026Yugo NakayamaSupport Vector MachinesClassification

    Independent researcher

  8. Post-Anomaly Detection Inference for Deep SVDD

    Sep 29, 2026Cao Le Cong Thanh, Dang Quang Vinh, Vo Nguyen Le DuySemi-Supervised Anomaly DetectionAnomaly Detection

    University of Information Technology, Ho Chi Minh City, Vietnam · Vietnam National University, Ho Chi Minh City, Vietnam

  9. Sharp margin-based generalization bounds for realizable SVM

    Sep 15, 2026Steve Hanneke, Aryeh KontorovichSupport Vector MachinesStatistical Learning Theory

  10. A family of spectral conjugate gradient algorithms derived by least-squares approximations based on a modified quasi--Newton update with application to a revised robust binary classification model

    Sep 11, 2026Saman Babaie-Kafaki, Maryam Khoshsimaye-Bargard, Ahmad MousaviRobust ClassificationNonconvex Optimization

    Faculty of Engineering, Free University of Bozen–Bolzano, 39100 Bolzano, Italy · Department of Mathematics, Faculty of Mathematics, Statistics and Computer Science, Semnan University, Semnan, Iran · Department of Mathematics and Statistics, American University, Washington, D.C., USA

  11. Common Geodesics Do Not Guarantee Fisher Consistency of the Structured SVM: Minimal Counterexamples and a Tree-Metric Classification

    Aug 27, 2026Jintao Fei, Jiangying LuoSupport Vector MachinesStructured Prediction

    Tsinghua University

  12. Data-Driven Time-Varying Control Barrier Functions for Adaptive Safe-Set Learning with Online Decremental Support Vector Machines

    Aug 19, 2026Shawon Dey, Michael Budihartono, Hever MoncayoSafety-Critical ControlControl Barrier Functions

    Department of Aerospace Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114 USA

  13. Convex losses and their applications to SVM, SVR, and Shallow Neural Networks

    Aug 14, 2026Filippo PorteraSupport Vector MachinesNeural Network Generalization

    DAIS, Università degli studi ”Ca’ Foscari” di Venezia, Italy

  14. Sparse and robust geometric twin support vector machine via asymmetric RoBoSS loss function

    Aug 12, 2026Kai Qi, Xinji Huang, Hongchun WangNoisy-Label LearningRobust Loss Functions

    National Center for Applied Mathematics in Chongqing, Chongqing Normal University, Chongqing, 401331, China. · School of Mathematical Sciences, Chongqing Normal University, Chongqing, 401331, China.

  15. Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning

    Aug 4, 2026Álvaro Sánchez-Paniagua Ríos, Juan P. Llerena, Alberto Lastra +2Support Vector MachinesKernel Methods

    Physics and Mathematics Department, University of Alcalá, Spain · Computer Science and Artificial Intelligence Department, University of Alcalá, Spain · Mathematics Department, Universidad Autónoma de Madrid, Spain

  16. Data-Driven Pinball-Loss Selection for Vertically Distributed Elastic-Net SVMs

    Aug 2, 2026Xiaofei Wu, Kai Qi, Rongmei LiangDistributed OptimizationAdaptive Loss Weighting

    Yunnan Key Laboratory of Statistical Modeling and Data Analysis, School of Mathematics and Statistics, Yunnan University, East Outer Ring South Road, University Town, Chenggong District, Kunming, Yunnan, China · National Center for Applied Mathematics in Chongqing, Chongqing Normal University, No. 37 University Town Middle Road, Shapingba District, Chongqing, China · Department of Statistics and Data Science, Southern University of Science and Technology, 1088 Xueyuan Avenue, Nanshan District, Shenzhen, Guangdong 518055, China

  17. Formulation-Level Auto-Tuning for QUBO-Based Machine Learning: A Case Study Across Multiple Quantum-Inspired Annealers

    Jul 21, 2026Naoya Mizuki, Takahiro Katagiri, Daichi Mukunoki +1Black-Box OptimizationQuantum-Inspired ML

    Graduate School of Informatics, Nagoya University · Information Technology Center, Nagoya University

  18. An Iterative Geometric Approach to Optimizing Separating Hyperplanes

    Jul 19, 2026Akos HajnalSupport Vector MachinesConstrained Optimization

    Laboratory of Parallel and Distributed Systems Institute for Computer Science and Control (SZTAKI) · John von Neumann Faculty of Informatics Obuda University Budapest, Hungary

  19. Differential Spectral Damping Gap Adaptive Regularization for Ill-Conditioned Kernel Methods

    Jun 22, 2026Praveg VashishthaSpectral RegularizationSupport Vector Machines

    Department of Computer Science and Engineering, Indian Institute of Technology Patna, India · Sopra Banking Software India

  20. Sequential Minimal Optimization Algorithm for One-Class Support Vector Machines With Privileged Information

    Jun 20, 2026Andrey Lange, Dmitry Smolyakov, Evgeny BurnaevSupport Vector MachinesOne-Class Classification

    Skolkovo Institute of Science and Technology (Skoltech), Moscow 121205, Russia · Federal Research Center ‘‘Computer Science and Control" of Russian Academy of Sciences (FRC CSC RAS), Moscow 119333, Russia · Institute for Information Transmission Problems of Russian Academy of Sciences (IITP RAS), 127994 Moscow, Russia +1

  21. Decomposing one-class support vector machine into an ensemble of one-data support vector machines

    Jun 14, 2026Toshitaka Hayashi, Dalibor Cimr, Hamido Fujita +1Support Vector MachinesClassification

    Faculty of Science, University of Hradec Kralove, Hradecká 1285, Hradec Kralove, 50003, Czech Republic · Malaysia-Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, Kampung Datuk Keramat, Kuala Lumpur, 54100, Malaysia · Regional Research Center, Iwate Prefectural University, Sugo 152-52, Takizawa, 020-0693, Iwate, Japan

  22. TorchKM: A GPU-Oriented Library for Kernel Learning and Model Selection

    Jun 4, 2026Yikai Zhang, Gaoxiang Jia, Jie Ding +1Model SelectionKernel Regression

    Department of Statistics and Actuarial Science, University of Iowa, Iowa City, IA 52242, USA · Individual Researcher · AIScientists, Inc. (MorphMind), 245 Main Street, Cambridge, MA 02142, USA

  23. Robust and sparse support vector machine via hybrid truncated loss for supervised classification

    Jun 4, 2026Yuliang Yang, Chen Chen, Yuxiang Liu +1Multi-View LearningRobust Loss Functions

    School of Science, Beijing Forestry University, No.35 Qinghua East Road, 100083 Haidian, Beijing, China · Translational Cancer Research Center, Peking University First Hospital, No. 8 Xishiku Street, 100034 Xicheng, Beijing, China

  24. Intercomparison of Machine Learning Algorithms for Remote Sensing-based In-season Crop Mapping

    Jun 4, 2026August Posch, Jitendra Kumar, Forrest M. Hoffman +1Agricultural Remote SensingRemote Sensing

    Institute for Experiential Artificial Intelligence and Sustainability and Data Sciences Lab, Northeastern University, 216 Massachusetts Avenue, Boston, MA 02155 USA · Environmental Sciences Division, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37830 USA · Computational Science and Engineering Division, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37830 USA

  25. Graph-Guided Universum Learning in Generalized Eigenvalue Proximal SVMs for Alzheimer's Disease Classification

    Jun 3, 2026Yogesh Kumar, Vrushank Ahire, Mudasir GanaieAlzheimer's DiseaseMedical Image Classification

    Dept. of Computer Science and Engineering, IIT Ropar, Punjab 140001, India

  26. Analytical Evaluation of DCA Convergence Properties for Minimizing Prediction Functions of Gaussian RBF Support Vector Regression

    Jun 2, 2026Yohei Kakimoto, Yuto Omae, Hirotaka TakahashiOptimization Convergence AnalysisSupport Vector Machines

    Nihon University · Tokyo City University

  27. Out-of-Distribution generalization of quantile regression with heavy tailed inputs: an SVM approach

    May 29, 2026Baptiste Leroux, Clément Dombry, Anne SabourinQuantile RegressionOOD Generalization

    Université Paris Cité, CNRS, MAP5, F-75006 Paris, France · Université Marie et Louis Pasteur, CNRS, LmB (UMR 6623), F-25000 Besançon, France · Université Paris Cité, Université Paris Saclay, ENS Paris Saclay, CNRS, SSA, INSERM, Centre Borelli, F-75006, Paris, France

  28. Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations

    May 21, 2026Artur MiroszewskiAdaptive SamplingSupport Vector Machines

    Φ-lab, European Space Agency (ESA/ESRIN), Frascati, Italy

  29. Optimised Support Vector Regression for California Housing Price Prediction: The Critical Role of Feature Engineering and Hyperparameter Tuning

    May 9, 2026Emmanuel AdutwumSupport Vector MachinesHyperparameter Optimization

    Soka University of America, Aliso Viejo, California, United States.

  30. A Comparative Analysis of Classical Machine Learning and Deep Learning Approaches for Sentiment Classification on IMDb Movie Reviews

    May 8, 2026Erma Daniar Safitri, Lia Hana Ichisasmita, Citra Agustin +3Sentiment AnalysisSupport Vector Machines

    Department of Data Science Institut Teknologi Sumatera Lampung Selatan, 35365, Indonesia · Department of Informatics Engineering Institut Teknologi Sumatera Lampung Selatan, 35365, Indonesia