4 papers
Personalized Product Search Ranking: A Multi-Task Learning Approach with Tabular and Non-Tabular Data
Lalitesh Morishetti, Abhay Kumar, Jonathan Scott +6
In this paper, we present a novel model architecture for optimizing personalized product search ranking using a multi-task learning (MTL) framework. Our approach uniquely integrate…
Differentially Private Federated -Means Clustering with Server-Side Data
Jonathan Scott, Christoph H. Lampert, David Saulpic
Clustering is a cornerstone of data analysis that is particularly suited to identifying coherent subgroups or substructures in unlabeled data, as are generated continuously in larg…
Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions
Hossein Zakerinia, Jonathan Scott, Christoph H. Lampert
Personalized federated learning has emerged as a popular approach to training on devices holding statistically heterogeneous data, known as clients. However, most existing approach…
PeFLL: Personalized Federated Learning by Learning to Learn
Jonathan Scott, Hossein Zakerinia, Christoph H. Lampert
We present PeFLL, a new personalized federated learning algorithm that improves over the state-of-the-art in three aspects: 1) it produces more accurate models, especially in the l…