3 papers
cs.LG2025
AutoNFS: Automatic Neural Feature Selection
Witold Wydmański, Marek Śmieja
Feature selection (FS) is a fundamental challenge in machine learning, particularly for high-dimensional tabular data, where interpretability and computational efficiency are criti…
cs.LG2025
VisTabNet: Adapting Vision Transformers for Tabular Data
Witold Wydmański, Ulvi Movsum-zada, Jacek Tabor +1
Although deep learning models have had great success in natural language processing and computer vision, we do not observe comparable improvements in the case of tabular data, whic…
cs.IR2024
Machine Unlearning for Recommendation Systems: An Insight
Bhavika Sachdeva, Harshita Rathee, Sristi +2
This review explores machine unlearning (MUL) in recommendation systems, addressing adaptability, personalization, privacy, and bias challenges. Unlike traditional models, MUL dyna…