94 citations · 355 across the 30 of their papers we have counts for
8 papers · 1 filter
Personalized Federated Learning through Local Memorization
Othmane Marfoq, Giovanni Neglia, Laetitia Kameni +1
Federated learning allows clients to collaboratively learn statistical models while keeping their data local. Federated learning was originally used to train a unique global model…
Efficient passive membership inference attack in federated learning
Oualid Zari, Chuan Xu, Giovanni Neglia
In cross-device federated learning (FL) setting, clients such as mobiles cooperate with the server to train a global machine learning model, while maintaining their data locally. H…
Federated Multi-Task Learning under a Mixture of Distributions
Othmane Marfoq, Giovanni Neglia, Aurélien Bellet +2
The increasing size of data generated by smartphones and IoT devices motivated the development of Federated Learning (FL), a framework for on-device collaborative training of machi…
Ascent Similarity Caching with Approximate Indexes
T. Si-Salem, G. Neglia, D. Carra
Similarity search is a key operation in multimedia retrieval systems and recommender systems, and it will play an important role also for future machine learning and augmented real…
A New Upper Bound on Cache Hit Probability for Non-anticipative Caching Policies
Nitish K. Panigrahy, Philippe Nain, Giovanni Neglia +1
Caching systems have long been crucial for improving the performance of a wide variety of network and web based online applications. In such systems, end-to-end application perform…
Towards Inference Delivery Networks: Distributing Machine Learning with Optimality Guarantees
T. Si Salem, G. Castellano, G. Neglia +2
An increasing number of applications rely on complex inference tasks that are based on machine learning (ML). Currently, there are two options to run such tasks: either they are se…
Content Placement in Networks of Similarity Caches
Michele Garetto, Emilio Leonardi, Giovanni Neglia
Similarity caching systems have recently attracted the attention of the scientific community, as they can be profitably used in many application contexts, like multimedia retrieval…
No-Regret Caching via Online Mirror Descent
T. Si Salem, G. Neglia, S. Ioannidis
We study an online caching problem in which requests can be served by a local cache to avoid retrieval costs from a remote server. The cache can update its state after a batch of r…