3 papers
cs.LG2025
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis
Sijia Zhou, Yunwen Lei, Ata Kabán
We study stochastic optimization with data-adaptive sampling schemes to train pairwise learning models. Pairwise learning is ubiquitous, and it covers several popular learning task…
cs.LG2023
Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension
Efstratios Palias, Ata Kabán
Metric learning aims at finding a suitable distance metric over the input space, to improve the performance of distance-based learning algorithms. In high-dimensional settings, it…
cs.LG2022
Approximability and Generalisation
Andrew J. Turner, Ata Kabán
Approximate learning machines have become popular in the era of small devices, including quantised, factorised, hashed, or otherwise compressed predictors, and the quest to explain…