3 papers
cs.LG2024
Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging
Hilal AlQuabeh, William de Vazelhes, Bin Gu
Pairwise learning, an important domain within machine learning, addresses loss functions defined on pairs of training examples, including those in metric learning and AUC maximizat…
cs.LG2023
Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory
Hilal AlQuabeh, Bhaskar Mukhoty, Bin Gu
Pairwise learning is essential in machine learning, especially for problems involving loss functions defined on pairs of training examples. Online gradient descent (OGD) algorithms…
cs.LG2022
Pairwise Learning via Stagewise Training in Proximal Setting
Hilal AlQuabeh, Aliakbar Abdurahimov
The pairwise objective paradigms are an important and essential aspect of machine learning. Examples of machine learning approaches that use pairwise objective functions include di…