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Found 6 papers, 1 papers with code
Fairness-aware Differentially Private Collaborative Filtering
Recently, there has been an increasing adoption of differential privacy guided algorithms for privacy-preserving machine learning tasks.
Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion Model
Diffusion Denoising Probability Models (DDPM) and Vision Transformer (ViT) have demonstrated significant progress in generative tasks and discriminative tasks, respectively, and thus far these models have largely been developed in their own domains.
Toward Pareto Efficient Fairness-Utility Trade-off inRecommendation through Reinforcement Learning
One conspicuous approach is to seek a Pareto efficient solution to guarantee optimal compromises between utility and fairness.
Learning Item-Interaction Embeddings for User Recommendations
Industry-scale recommendation systems have become a cornerstone of the e-commerce shopping experience.
Clustering via Content-Augmented Stochastic Blockmodels
Much of the data being created on the web contains interactions between users and items.
A Markov Decision Process Analysis of the Cold Start Problem in Bayesian Information Filtering
We focus on the cold-start setting for this problem, in which we have limited historical data on the user's preferences, and must rely on feedback from forwarded articles to learn which the fraction of items relevant to the user in each of several item categories.
