![Collaborative Filtering Unleashed: A Study on Adversarial Approaches (arXiv:2308.13541v1 [cs.IR])](https://instadatanews.com/wp-content/uploads/2023/08/arxiv-logo-fb-1080x675.png)
by instadatahelp | Aug 29, 2023 | AI Blogs
Collaborative Filtering (CF) has been successfully utilized to assist users in discovering items of interest. However, existing CF methods are hindered by the issue of noisy data, which negatively affects the quality of recommendations. To address this problem,...
by instadatahelp | Aug 29, 2023 | AI Blogs
Contextual Stochastic Block Model: Sharp Thresholds and Contiguity Chen Lu, Subhabrata Sen; 24(54):1−34, 2023. Abstract This study focuses on community detection in the “contextual stochastic block model” (Yan and Sarkar, 2020; Deshpande et al., 2018)....
by instadatahelp | Aug 29, 2023 | AI Blogs
Lifted Bregman Training of Neural Networks Xiaoyu Wang, Martin Benning; 24(232):1−51, 2023. Abstract A new mathematical formulation is introduced for training feed-forward neural networks with potentially non-smooth proximal maps as activation functions. This...
by instadatahelp | Aug 29, 2023 | AI Blogs
Multi-task learning (MTL) has become increasingly popular in recommendation systems as it allows for the simultaneous optimization of multiple objectives. However, a major challenge in MTL is negative transfer, where the performance of certain tasks deteriorates due...
by instadatahelp | Aug 29, 2023 | AI Blogs
Monotonic Alpha-divergence Minimisation for Variational Inference Kamélia Daudel, Randal Douc, François Roueff; 24(62):1−76, 2023. Abstract This paper presents a new family of iterative algorithms designed for minimizing alpha-divergence in the context of Variational...
