Universum Learning for SVM Regression

2016-05-27 · Sauptik Dhar, Vladimir Cherkassky

This paper extends the idea of Universum learning [18, 19] to regression problems. We propose new Universum-SVM formulation for regression problems that incorporates a priori knowledge in the form of additional data samples. These additional data samples or Universum belong to the same application domain as the training samples, but they follow a different distribution. Several empirical comparisons are presented to illustrate the utility of the proposed approach.

📄 PDF Abstract BibTeX arXiv:1605.08497

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regression

Universum-inspired Supervised Contrastive Learning

2022-04-22 · Aiyang Han, Chuanxing Geng, Songcan Chen

As an effective data augmentation method, Mixup synthesizes an extra amount of samples through linear interpolations. Despite its theoretical dependency on data properties, Mixup reportedly performs well as a regularizer…

Contrastive Learning Data Augmentation

Universum Learning for Multiclass SVM

2016-09-29 · Sauptik Dhar, Naveen Ramakrishnan, Vladimir Cherkassky, Mohak Shah

We introduce Universum learning for multiclass problems and propose a novel formulation for multiclass universum SVM (MU-SVM). We also propose a span bound for MU-SVM that can be used for model selection thereby avoiding…

Model Selection

A Unified Framework for EEG Seizure Detection Using Universum-Integrated Generalized Eigenvalues Proximal Support Vector Machine

2025-12-24 · Yogesh Kumar, Vrushank Ahire, M. A. Ganaie arxiv

The paper presents novel Universum-enhanced classifiers: the Universum Generalized Eigenvalue Proximal Support Vector Machine (U-GEPSVM) and the Improved U-GEPSVM (IU-GEPSVM) for EEG signal classification. Using the comp…

EEG Signal Classification Computational Efficiency Binary Classification Seizure Detection

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

2026-06-03 · Yogesh Kumar, Vrushank Ahire, Mudasir Ganaie arxiv

Early and accurate detection of Alzheimer's disease (AD) is important for timely intervention and disease management. Generalized Eigenvalue Proximal Support Vector Machine (GEPSVM) and its Universum-based variants have …

Single Class Universum-SVM

2019-09-21 · Sauptik Dhar, Vladimir Cherkassky

This paper extends the idea of Universum learning [1, 2] to single-class learning problems. We propose Single Class Universum-SVM setting that incorporates a priori knowledge (in the form of additional data samples) into…

Binary Classification