James Geraci

According to our database, James Geraci authored at least 7 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Hybrid Decentralised Learning Topology for Recommendations with Improved Privacy.

Diarmuid O'Reilly-Morgan, Elias Z. Tragos, James Geraci, Qinqin Wang, Neil Hurley, Barry Smyth, Aonghus Lawlor

Proceedings of the 4th Workshop on Machine Learning and Systems, 2024

ALS Algorithm for Robust and Communication-Efficient Federated Learning.

Neil Hurley, Erika Duriakova, James Geraci, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Barry Smyth, Aonghus Lawlor

Proceedings of the 4th Workshop on Machine Learning and Systems, 2024

2023

Keeping People Active and Healthy at Home Using a Reinforcement Learning-based Fitness Recommendation Framework.

Elias Z. Tragos, Diarmuid O'Reilly-Morgan, James Geraci, Bichen Shi, Barry Smyth, Cailbhe Doherty, Aonghus Lawlor, Neil Hurley

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2020

An Algorithmic Framework for Decentralised Matrix Factorisation.

Erika Duriakova, Weipéng Huáng, Elias Z. Tragos, Aonghus Lawlor, Barry Smyth, James Geraci, Neil Hurley

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems.

Khalil Muhammad, Qinqin Wang, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Barry Smyth, Neil Hurley, James Geraci, Aonghus Lawlor

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

PyRecGym: a reinforcement learning gym for recommender systems.

Bichen Shi, Makbule Gulcin Ozsoy, Neil Hurley, Barry Smyth, Elias Z. Tragos, James Geraci, Aonghus Lawlor

Proceedings of the 13th ACM Conference on Recommender Systems, 2019

PDMFRec: a decentralised matrix factorisation with tunable user-centric privacy.

Erika Duriakova, Elias Z. Tragos, Barry Smyth, Neil Hurley, Francisco J. Peña, Panagiotis Symeonidis, James Geraci, Aonghus Lawlor

Proceedings of the 13th ACM Conference on Recommender Systems, 2019