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05/12/2023
High Accuracy and Low Regret for User-Cold-Start Using Latent Bandits
We develop a novel latent-bandit algorithm for tackling the cold-start p...
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05/08/2023
Evaluating Impact of User-Cluster Targeted Attacks in Matrix Factorisation Recommenders
In practice, users of a Recommender System (RS) fall into a few clusters...
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02/01/2023
Bandit Convex Optimisation Revisited: FTRL Achieves Õ(t^1/2) Regret
We show that a kernel estimator using multiple function evaluations can ...
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10/30/2022
Two Models are Better than One: Federated Learning Is Not Private For Google GBoard Next Word Prediction
In this paper we present new attacks against federated learning when use...
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04/20/2022
Online Caching with no Regret: Optimistic Learning via Recommendations
The design of effective online caching policies is an increasingly impor...
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02/22/2022
Online Caching with Optimistic Learning
The design of effective online caching policies is an increasingly impor...
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04/03/2020
Universal Algorithms: Beyond the Simplex
The bulk of universal algorithms in the online convex optimisation liter...
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09/10/2019
Optimality of the Subgradient Algorithm in the Stochastic Setting
Recently Jaouad Mourtada and Stéphane Gaïffas showed the anytime hedge a...
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11/27/2018
3PS - Online Privacy through Group Identities
Limiting online data collection to the minimum required for specific pur...
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08/07/2018
Low Delay Scheduling of Objects Over Multiple Wireless Paths
In this paper we consider the task of scheduling packet transmissions am...
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04/13/2018
Joint Scheduling and Coding Over Lossy Paths With Delayed Feedback
We consider the transmission of packets across a lossy end-to-end networ...
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12/07/2017