28 citations · 94 across the 23 of their papers we have counts for
6 papers · 1 filter
Twin Restricted Kernel Machines for Multiview Classification
A. Quadir, M. Sajid, Mushir Akhtar +1
Multi-view learning (MVL) is an emerging field in machine learning that focuses on improving generalization performance by leveraging complementary information from multiple perspe…
RVFL-X: A Novel Randomized Network Based on Complex Transformed Real-Valued Tabular Datasets
M. Sajid, Mushir Akhtar, A. Quadir +1
Recent advancements in neural networks, supported by foundational theoretical insights, emphasize the superior representational power of complex numbers. However, their adoption in…
Hypergraph Neural Network with State Space Models for Node Classification
A. Quadir, M. Tanveer
In recent years, graph neural networks (GNNs) have gained significant attention for node classification tasks on graph-structured data. However, traditional GNNs primarily focus on…
Randomized based restricted kernel machine for hyperspectral image classification
A. Quadir, M. Tanveer
In recent years, the random vector functional link (RVFL) network has gained significant popularity in hyperspectral image (HSI) classification due to its simplicity, speed, and st…
One Class Restricted Kernel Machines
A. Quadir, M. Sajid, M. Tanveer
Restricted kernel machines (RKMs) have demonstrated a significant impact in enhancing generalization ability in the field of machine learning. Recent studies have introduced variou…
TRKM: Twin Restricted Kernel Machines for Classification and Regression
A. Quadir, M. Tanveer
Restricted kernel machines (RKMs) have considerably improved generalization in machine learning. Recent advancements explored various techniques within the RKM framework, integrati…