Aonghus Lawlor

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 60

Top Topics

Collaborative Filtering

Matrix Factorisation

Music Genre Classification

Top Venues

Publications

Niamh Belton, Aonghus Lawlor, Kathleen M. Curran
An AI System for Continuous Knee Osteoarthritis Severity Grading Using Self-Supervised Anomaly Detection with Limited Data. CoRR (2024)
Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
Towards a unified approach for unsupervised brain MRI Motion Artefact Detection with few shot Anomaly Detection. Comput. Medical Imaging Graph. 115 (2024)
Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
Rethinking Knee Osteoarthritis Severity Grading: A Few Shot Self-Supervised Contrastive Learning Approach. CoRR (2024)
Siteng Ma, Prateek Mathur, Zheng Ju, Aonghus Lawlor, Ruihai Dong
Model-data-driven adversarial active learning for brain tumor segmentation. Comput. Biol. Medicine 176 (2024)
Neil Hurley, Erika Duriakova, James Geraci, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Barry Smyth, Aonghus Lawlor
ALS Algorithm for Robust and Communication-Efficient Federated Learning. EuroMLSys@EuroSys (2024)
Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
A Case-Based Reasoning Approach to Post-injury Training Recommendations for Marathon Runners. ICCBR (2024)
Daniel Anojan Atputharuban, Christoph Theopold, Aonghus Lawlor
Enhancing Surgical Visualization: Feasibility Study on GAN-Based Image Generation for Post Operative Cleft Palate Images. ICPRAM (2024)
Siteng Ma, Haochang Wu, Aonghus Lawlor, Ruihai Dong
Breaking the Barrier: Selective Uncertainty-based Active Learning for Medical Image Segmentation. CoRR (2024)
Diarmuid O'Reilly-Morgan, Elias Z. Tragos, James Geraci, Qinqin Wang, Neil Hurley, Barry Smyth, Aonghus Lawlor
A Hybrid Decentralised Learning Topology for Recommendations with Improved Privacy. EuroMLSys@EuroSys (2024)
Siteng Ma, Haochang Wu, Aonghus Lawlor, Ruihai Dong
Breaking the Barrier: Selective Uncertainty-Based Active Learning for Medical Image Segmentation. ICASSP (2024)
Siteng Ma, Yu An, Jing Wang, Aonghus Lawlor, Ruihai Dong
Adaptive Adversarial Samples Based Active Learning for Medical Image Classification. ICPRAM (2023)
Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
FewSOME: One-Class Few Shot Anomaly Detection with Siamese Networks. CVPR Workshops (2023)
Haiwen Du, Zheng Ju, Yu An, Honghui Du, Dongjie Zhu, Zhaoshuo Tian, Aonghus Lawlor, Ruihai Dong
Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated Cases. CoRR (2023)
Edoardo D'Amico, Aonghus Lawlor, Neil Hurley
Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation. CoRR (2023)
Edoardo D'Amico, Khalil Muhammad, Elias Z. Tragos, Barry Smyth, Neil Hurley, Aonghus Lawlor
Item Graph Convolution Collaborative Filtering for Inductive Recommendations. CoRR (2023)
Elias Z. Tragos, Diarmuid O'Reilly-Morgan, James Geraci, Bichen Shi, Barry Smyth, Cailbhe Doherty, Aonghus Lawlor, Neil Hurley
Keeping People Active and Healthy at Home Using a Reinforcement Learning-based Fitness Recommendation Framework. IJCAI (2023)
Aayush Singha Roy, Edoardo D'Amico, Aonghus Lawlor, Neil Hurley
Addressing Fast Changing Fashion Trends in Multi-Stage Recommender Systems. FLAIRS (2023)
Aayush Singha Roy, Edoardo D'Amico, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley
Scalable Deep Q-Learning for Session-Based Slate Recommendation. RecSys (2023)
Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
Modelling the Training Practices of Recreational Marathon Runners to Make Personalised Training Recommendations. UMAP (2023)
Dairui Liu, Boming Yang, Honghui Du, Derek Greene, Aonghus Lawlor, Ruihai Dong, Irene Li
RecPrompt: A Prompt Tuning Framework for News Recommendation Using Large Language Models. CoRR (2023)
Edoardo D'Amico, Aonghus Lawlor, Neil Hurley
Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation. PAKDD (3) (2023)
Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
FewSOME: Few Shot Anomaly Detection. CoRR (2023)
Haiwen Du, Zheng Ju, Yu An, Honghui Du, Dongjie Zhu, Zhaoshuo Tian, Aonghus Lawlor, Ruihai Dong
Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated Cases. ICONIP (15) (2023)
Edoardo D'Amico, Khalil Muhammad, Elias Z. Tragos, Barry Smyth, Neil Hurley, Aonghus Lawlor
Item Graph Convolution Collaborative Filtering for Inductive Recommendations. ECIR (1) (2023)
Qinqin Wang, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Neil Hurley, Barry Smyth, Aonghus Lawlor, Ruihai Dong
Learning Domain-Independent Representations via Shared Weight Auto-Encoder for Transfer Learning in Recommender Systems. IEEE Access 10 (2022)
Qinqin Wang, Khalil Muhammad, Diarmuid O'Reilly-Morgan, Barry Smyth, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley, Ruihai Dong
MARF: User-Item Mutual Aware Representation with Feedback. ICWE (2022)
Barry Smyth, Aonghus Lawlor, Jakim Berndsen, Ciara Feely
Recommendations for marathon runners: on the application of recommender systems and machine learning to support recreational marathon runners. User Model. User Adapt. Interact. 32 (5) (2022)
Qinqin Wang, Elias Z. Tragos, Neil Hurley, Barry Smyth, Aonghus Lawlor, Ruihai Dong
Entity-Enhanced Graph Convolutional Network for Accurate and Explainable Recommendation. UMAP (2022)
Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
An Extended Case-Based Approach to Race-Time Prediction for Recreational Marathon Runners. ICCBR (2022)
Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
A Case-Based Reasoning Approach to Predicting and Explaining Running Related Injuries. ICCBR (2021)
Niamh Belton, Ivan Welaratne, Adil Dahlan, Ronan T. Hearne, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
Optimising Knee Injury Detection with Spatial Attention and Validating Localisation Ability. MIUA (2021)
Niamh Belton, Aonghus Lawlor, Kathleen M. Curran
Semi-Supervised Siamese Network for Identifying Bad Data in Medical Imaging Datasets. CoRR (2021)
Niamh Belton, Ivan Welaratne, Adil Dahlan, Ronan T. Hearne, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
Optimising Knee Injury Detection with Spatial Attention and Validating Localisation Ability. CoRR (2021)
Bichen Shi, Elias Z. Tragos, Makbule Gulcin Ozsoy, Ruihai Dong, Neil Hurley, Barry Smyth, Aonghus Lawlor
DARES: An Asynchronous Distributed Recommender System Using Deep Reinforcement Learning. IEEE Access 9 (2021)
Erika Duriakova, Elias Z. Tragos, Aonghus Lawlor, Barry Smyth, Neil Hurley
Boosting the Training Time of Weakly Coordinated Distributed Machine Learning. IEEE BigData (2021)
Sixun Ouyang, Aonghus Lawlor
Improving Explainable Recommendations by Deep Review-Based Explanations. IEEE Access 9 (2021)
Erika Duriakova, Weipéng Huáng, Elias Z. Tragos, Aonghus Lawlor, Barry Smyth, James Geraci, Neil Hurley
An Algorithmic Framework for Decentralised Matrix Factorisation. ECML/PKDD (2) (2020)
Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
Using Case-Based Reasoning to Predict Marathon Performance and Recommend Tailored Training Plans. ICCBR (2020)
Jakim Berndsen, Barry Smyth, Aonghus Lawlor
Fit to Run: Personalised Recommendations for Marathon Training. RecSys (2020)
Jakim Berndsen, Barry Smyth, Aonghus Lawlor
A Collaborative Filtering Approach to Successfully Completing The Marathon. ICMLA (2020)
Jakim Berndsen, Barry Smyth, Aonghus Lawlor
Mining Marathon Training Data to Generate Useful User Profiles. MLSA@PKDD/ECML (2020)
Khalil Muhammad, Qinqin Wang, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Barry Smyth, Neil Hurley, James Geraci, Aonghus Lawlor
FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems. KDD (2020)
Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
Providing Explainable Race-Time Predictions and Training Plan Recommendations to Marathon Runners. RecSys (2020)
Francisco J. Peña, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Neil Hurley, Erika Duriakova, Barry Smyth, Aonghus Lawlor
Combining Rating and Review Data by Initializing Latent Factor Models with Topic Models for Top-N Recommendation. RecSys (2020)
Makbule Gulcin Ozsoy, Diarmuid O'Reilly-Morgan, Panagiotis Symeonidis, Elias Z. Tragos, Neil Hurley, Barry Smyth, Aonghus Lawlor
MP4Rec: Explainable and Accurate Top-N Recommendations in Heterogeneous Information Networks. IEEE Access 8 (2020)
Cataldo Musto, Amon Rapp, Federica Cena, Frank Hopfgartner, Judy Kay, Aonghus Lawlor, Pasquale Lops, Giovanni Semeraro, Nava Tintarev
UMAP 2019 Workshop on Explainable and Holistic User Modeling (ExHUM) Chairs' Welcome & Organization. UMAP (Adjunct Publication) (2019)
Jakim Berndsen, Barry Smyth, Aonghus Lawlor
Pace my race: recommendations for marathon running. RecSys (2019)
Sixun Ouyang, Aonghus Lawlor
NEAR: A Partner to Explain Any Factorised Recommender System. UMAP (Adjunct Publication) (2019)
Erika Duriakova, Elias Z. Tragos, Barry Smyth, Neil Hurley, Francisco J. Peña, Panagiotis Symeonidis, James Geraci, Aonghus Lawlor
PDMFRec: a decentralised matrix factorisation with tunable user-centric privacy. RecSys (2019)
Bichen Shi, Makbule Gulcin Ozsoy, Neil Hurley, Barry Smyth, Elias Z. Tragos, James Geraci, Aonghus Lawlor
PyRecGym: a reinforcement learning gym for recommender systems. RecSys (2019)
Sixun Ouyang, Aonghus Lawlor, Felipe Costa, Peter Dolog
Improving Explainable Recommendations with Synthetic Reviews. CoRR (2018)
Khalil Muhammad, Aonghus Lawlor, Barry Smyth
A Multi-Domain Analysis of Explanation-Based Recommendation using User-Generated Reviews. FLAIRS Conference (2018)
Felipe Costa, Sixun Ouyang, Peter Dolog, Aonghus Lawlor
Automatic Generation of Natural Language Explanations. IUI Companion (2018)
Felipe Costa, Sixun Ouyang, Peter Dolog, Aonghus Lawlor
Automatic Generation of Natural Language Explanations. CoRR (2017)
Jakim Berndsen, Aonghus Lawlor, Barry Smyth
Running with Recommendation. HealthRecSys@RecSys (2017)
Khalil Muhammad, Aonghus Lawlor, Barry Smyth
On the Pros and Cons of Explanation-Based Ranking. ICCBR (2017)
Khalil Muhammad, Aonghus Lawlor, Barry Smyth
Explanation-based Ranking in Opinionated Recommender Systems. AICS (2016)
Sergio Oramas, Luis Espinosa Anke, Aonghus Lawlor, Xavier Serra, Horacio Saggion
Exploring Customer Reviews for Music Genre Classification and Evolutionary Studies. ISMIR (2016)
Khalil Muhammad, Aonghus Lawlor, Barry Smyth
On the Use of Opinionated Explanations to Rank and Justify Recommendations. FLAIRS Conference (2016)
Khalil Ibrahim Muhammad, Aonghus Lawlor, Barry Smyth
A Live-User Study of Opinionated Explanations for Recommender Systems. IUI (2016)
Aonghus Lawlor, Khalil Muhammad, Rachael Rafter, Barry Smyth
Opinionated Explanations for Recommendation Systems. SGAI Conf. (2015)
Khalil Muhammad, Aonghus Lawlor, Rachael Rafter, Barry Smyth
Generating Personalised and Opinionated Review Summaries. UMAP Workshops (2015)
Khalil Muhammad, Aonghus Lawlor, Rachael Rafter, Barry Smyth
Great Explanations: Opinionated Explanations for Recommendations. ICCBR (2015)
Doychin Doychev, Rachael Rafter, Aonghus Lawlor, Barry Smyth
News Recommenders: Real-Time, Real-Life Experiences. UMAP (2015)
Gavin McArdle, Eoghan Furey, Aonghus Lawlor, Alexei Pozdnoukhov
Using Digital Footprints for a City-Scale Traffic Simulation. ACM Trans. Intell. Syst. Technol. 5 (3) (2014)
Doychin Doychev, Aonghus Lawlor, Rachael Rafter
An Analysis of Recommender Algorithms for Online News. CLEF (Working Notes) (2014)
Gavin McArdle, Aonghus Lawlor, Eoghan Furey, Alexei Pozdnoukhov
City-scale traffic simulation from digital footprints. UrbComp@KDD (2012)
Paolo De Gregorio, Aonghus Lawlor, Phil Bradley, Kenneth A. Dawson
Cellular Automata with Rare Events; Resolution of an Outstanding Problem in the Bootstrap Percolation Model. ACRI (2004)