Search Results for author: Stephen Hardy

Found 3 papers, 0 papers with code

Entity Resolution and Federated Learning get a Federated Resolution

no code implementations11 Mar 2018 Richard Nock, Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Giorgio Patrini, Guillaume Smith, Brian Thorne

In our experiments, we modify a simple token-based entity resolution algorithm so that it indeed aims at avoiding matching rows belonging to different classes, and perform experiments in the setting where entity resolution relies on noisy data, which is very relevant to real world domains.

Entity Resolution Federated Learning +1

Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption

no code implementations29 Nov 2017 Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Richard Nock, Giorgio Patrini, Guillaume Smith, Brian Thorne

Our results bring a clear and strong support for federated learning: under reasonable assumptions on the number and magnitude of entity resolution's mistakes, it can be extremely beneficial to carry out federated learning in the setting where each peer's data provides a significant uplift to the other.

Entity Resolution Federated Learning

Fast Learning from Distributed Datasets without Entity Matching

no code implementations13 Mar 2016 Giorgio Patrini, Richard Nock, Stephen Hardy, Tiberio Caetano

Our goal is to learn a classifier in the cross product space of the two domains, in the hard case in which no shared ID is available -- e. g. due to anonymization.

Entity Resolution

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