Cover Image

TRKM: Twin Restricted Kernel Machines for Classification and Regression

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Quadir, A., Tanveer, M.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Twin Restricted Kernel Machines for Multiview Classification
by: Quadir, A., et al.
Published: (2025)

One Class Restricted Kernel Machines
by: Quadir, A., et al.
Published: (2025)

Robust Universum Twin Support Vector Machine for Imbalanced Data
by: Tanveer, M., et al.
Published: (2024)

Granular Ball Twin Support Vector Machine
by: Quadir, A., et al.
Published: (2024)

Hypergraph Neural Network with State Space Models for Node Classification
by: Quadir, A., et al.
Published: (2025)

Enhanced Feature Based Granular Ball Twin Support Vector Machine
by: Quadir, A., et al.
Published: (2024)

Multiview learning with twin parametric margin SVM
by: Quadir, A., et al.
Published: (2024)

Intuitionistic Fuzzy Generalized Eigenvalue Proximal Support Vector Machine
by: Quadir, A., et al.
Published: (2024)

Enhancing Robustness and Efficiency of Least Square Twin SVM via Granular Computing
by: Tanveer, M., et al.
Published: (2024)

CI-RKM: A Class-Informed Approach to Robust Restricted Kernel Machines
by: Mishra, Ritik, et al.
Published: (2025)

Randomized based restricted kernel machine for hyperspectral image classification
by: Quadir, A., et al.
Published: (2025)

Wave-RVFL: A Randomized Neural Network Based on Wave Loss Function
by: Sajid, M., et al.
Published: (2024)

Enhancing Multiview Synergy: Robust Learning by Exploiting the Wave Loss Function with Consensus and Complementarity Principles
by: Quadir, A., et al.
Published: (2024)

Multiview Random Vector Functional Link Network for Predicting DNA-Binding Proteins
by: Quadir, A., et al.
Published: (2024)

GB-RVFL: Fusion of Randomized Neural Network and Granular Ball Computing
by: Sajid, M., et al.
Published: (2024)

Flexi-Fuzz least squares SVM for Alzheimer's diagnosis: Tackling noise, outliers, and class imbalance
by: Akhtar, Mushir, et al.
Published: (2024)

RVFL-X: A Novel Randomized Network Based on Complex Transformed Real-Valued Tabular Datasets
by: Sajid, M., et al.
Published: (2025)

GRVFL-MV: Graph Random Vector Functional Link Based on Multi-View Learning
by: Tanveer, M., et al.
Published: (2024)

HawkEye: Advancing Robust Regression with Bounded, Smooth, and Insensitive Loss Function
by: Akhtar, Mushir, et al.
Published: (2024)

Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning
by: He, Fan, et al.
Published: (2024)

Spectrally Transformed Kernel Regression
by: Zhai, Runtian, et al.
Published: (2024)

Granular-Balls based Fuzzy Twin Support Vector Machine for Classification
by: Zhao, Lixi, et al.
Published: (2024)

Double Machine Learning for Conditional Moment Restrictions: IV Regression, Proximal Causal Learning and Beyond
by: Shao, Daqian, et al.
Published: (2025)

Large Dimensional Kernel Ridge Regression: Extending to Product Kernels
by: Zhou, Yang, et al.
Published: (2026)

Diluting Restricted Boltzmann Machines
by: Díaz-Faloh, C., et al.
Published: (2025)

Bayesian Kernel Regression for Functional Data
by: Kusaba, Minoru, et al.
Published: (2025)

On the Saturation Effect of Kernel Ridge Regression
by: Li, Yicheng, et al.
Published: (2024)

Sparse Attention as Compact Kernel Regression
by: Santos, Saul, et al.
Published: (2026)

SPINEX: Similarity-based Predictions and Explainable Neighbors Exploration for Regression and Classification Tasks in Machine Learning
by: Naser, M. Z., et al.
Published: (2023)

Decoding Cognitive Health Using Machine Learning: A Comprehensive Evaluation for Diagnosis of Significant Memory Concern
by: Sajid, M., et al.
Published: (2024)

The Impact of Feature Scaling In Machine Learning: Effects on Regression and Classification Tasks
by: Pinheiro, João Manoel Herrera, et al.
Published: (2025)

Kernel Ridge Regression Inference
by: Singh, Rahul, et al.
Published: (2023)

Transfer Learning for Kernel-based Regression
by: Wang, Chao, et al.
Published: (2023)

Lepskii Principle for Distributed Kernel Ridge Regression
by: Lin, Shao-Bo
Published: (2024)

Tighter Confidence Bounds for Sequential Kernel Regression
by: Flynn, Hamish, et al.
Published: (2024)

Granular Ball Twin Support Vector Machine with Universum Data
by: Ganaie, M. A., et al.
Published: (2024)

Koopman Kernel Regression
by: Bevanda, Petar, et al.
Published: (2023)

Kernel-Free Universum Quadratic Surface Twin Support Vector Machines for Imbalanced Data
by: Moosaei, Hossein, et al.
Published: (2024)

The Neural Tangent Kernel for Classification
by: Plenk, Jonathan, et al.
Published: (2026)

LSTSVR-PI: Least square twin support vector regression with privileged information
by: Kumari, Anuradha, et al.
Published: (2023)