Aonghus Lawlor

97 papers A* 4A 17B 2C 11Misc 4Journal 27Unranked 31

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Don't Get Bored: Enhancing Scalability and Diversity in Session-Based Slate Recommendation. Trans. Recomm. Syst. Aayush Singha Roy, Edoardo D'Amico, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley
2026	J	`jnl`	DyABD: the abdominal muscle segmentation in dynamic MRI benchmark. BMC Medical Imaging Niamh Belton, Victoria Joppin, Aonghus Lawlor, Catherine Masson, Thierry Bège, David Bendahan, Kathleen M. Curran
2026	A	`conf`	Transfer Learning via User-Item Graph Convolution for Enhanced Cross-Domain Recommendation. WSDM Zheng Ju, Qinqin Wang, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Neil Hurley, Ruihai Dong, Aonghus Lawlor
2025	J	`jnl`	An AI system for continuous knee osteoarthritis severity grading: An anomaly detection inspired approach with few labels. Artif. Intell. Medicine Niamh Belton, Aonghus Lawlor, Kathleen M. Curran
2025	J	`jnl`	Deep Learning Approaches for Medical Imaging Under Varying Degrees of Label Availability: A Comprehensive Survey. CoRR Siteng Ma, Honghui Du, Yu An, Jing Wang, Qinqin Wang, Haochang Wu, Aonghus Lawlor, Ruihai Dong
2025	—	`conf`	DiffGR: A Discrete Diffusion-Based Model for Personalised Recommendation by Reconstructing User-Item Bipartite Graphs. ECIR (3) Zheng Ju, Honghui Du, Elias Z. Tragos, Neil Hurley, Aonghus Lawlor
2025	A	`conf`	EARL: The 2nd Workshop on Evaluating and Applying Recommender Systems with Large Language Models. RecSys Irene Li, Ruihai Dong, Guillaume Salha-Galvan, Aonghus Lawlor, Dairui Liu, Lei Li
2025	B	`conf`	Is Complete Labeling Necessary? Understanding Active Learning in Longitudinal Medical Imaging. IJCNN Siteng Ma, Honghui Du, Prateek Mathur, Brendan S. Kelly, Ronan P. Killeen, Aonghus Lawlor, Ruihai Dong
2025	J	`jnl`	Is Complete Labeling Necessary? Understanding Active Learning in Longitudinal Medical Imaging. CoRR Siteng Ma, Honghui Du, Prateek Mathur, Brendan S. Kelly, Ronan P. Killeen, Aonghus Lawlor, Ruihai Dong
2025	—	`conf`	Lesion-Aware CT-to-MRI Synthesis Using a Mask-Informed Diffusion with Adaptive-Weighted Loss (MIDAS). SASHIMI@MICCAI 2025 Prateek Mathur, Paul Banahan, Jane Burns, Peter MacMahon, Aonghus Lawlor
2025	A*	`conf`	Multi-Label Transfer Learning in Non-Stationary Data Streams. ICDM Honghui Du, Leandro L. Minku, Aonghus Lawlor, Huiyu Zhou
2025	J	`jnl`	Multi-Label Transfer Learning in Non-Stationary Data Streams. CoRR Honghui Du, Leandro L. Minku, Aonghus Lawlor, Huiyu Zhou
2025	A*	`conf`	NodeRec+: A Lightweight Framework for Federated Recommender Systems. SIGIR Diarmuid O'Reilly-Morgan, Erika Duriakova, Elias Z. Tragos, Neil Hurley, Aonghus Lawlor
2025	A	`conf`	SlateLLM: Distilling LLM Semantics into Session-Aware Slate Recommendation without Inference Overhead. RecSys Aayush Singha Roy, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley
2025	—	`conf`	Spatial Aggregation for Semi-supervised Active Learning in 3D Medical Image Segmentation. MICCAI (8) Siteng Ma, Honghui Du, Dairui Liu, Kathleen M. Curran, Aonghus Lawlor, Ruihai Dong
2025	C	`conf`	SplitFedEE: Balancing Communication and Accuracy. VCIP Erika Duriakova, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Neil Hurley, Aonghus Lawlor
2024	C	`conf`	A Case-Based Reasoning Approach to Post-injury Training Recommendations for Marathon Runners. ICCBR Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
2024	—	`conf`	A Hybrid Decentralised Learning Topology for Recommendations with Improved Privacy. EuroMLSys@EuroSys Diarmuid O'Reilly-Morgan, Elias Z. Tragos, James Geraci, Qinqin Wang, Neil Hurley, Barry Smyth, Aonghus Lawlor
2024	—	`conf`	ALS Algorithm for Robust and Communication-Efficient Federated Learning. EuroMLSys@EuroSys Neil Hurley, Erika Duriakova, James Geraci, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Barry Smyth, Aonghus Lawlor
2024	—	`conf`	Adaptive Curriculum Query Strategy for Active Learning in Medical Image Classification. MICCAI (11) Siteng Ma, Honghui Du, Kathleen M. Curran, Aonghus Lawlor, Ruihai Dong
2024	J	`jnl`	An AI System for Continuous Knee Osteoarthritis Severity Grading Using Self-Supervised Anomaly Detection with Limited Data. CoRR Niamh Belton, Aonghus Lawlor, Kathleen M. Curran
2024	Misc	`conf`	Breaking the Barrier: Selective Uncertainty-Based Active Learning for Medical Image Segmentation. ICASSP Siteng Ma, Haochang Wu, Aonghus Lawlor, Ruihai Dong
2024	J	`jnl`	Breaking the Barrier: Selective Uncertainty-based Active Learning for Medical Image Segmentation. CoRR Siteng Ma, Haochang Wu, Aonghus Lawlor, Ruihai Dong
2024	—	`conf`	CleftLipGAN : Interactive GAN-Inpainting for Post-Operative Cleft Lip Reconstruction. ACCV Workshops (1) Daniel Anojan Atputharuban, Christoph Theopold, Aonghus Lawlor
2024	C	`conf`	Enhancing Surgical Visualization: Feasibility Study on GAN-Based Image Generation for Post Operative Cleft Palate Images. ICPRAM Daniel Anojan Atputharuban, Christoph Theopold, Aonghus Lawlor
2024	—	`conf`	Entity Matching with Large Language Models as Weak and Strong Labellers. ADBIS (Short Papers) Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Erika Duriakova, Honghui Du, Neil Hurley, Aonghus Lawlor
2024	A	`conf`	Exploring Coresets for Efficient Training and Consistent Evaluation of Recommender Systems. RecSys Zheng Ju, Honghui Du, Elias Z. Tragos, Neil Hurley, Aonghus Lawlor
2024	J	`jnl`	Model-data-driven adversarial active learning for brain tumor segmentation. Comput. Biol. Medicine Siteng Ma, Prateek Mathur, Zheng Ju, Aonghus Lawlor, Ruihai Dong
2024	A	`conf`	RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Models. CIKM Dairui Liu, Boming Yang, Honghui Du, Derek Greene, Neil Hurley, Aonghus Lawlor, Ruihai Dong, Irene Li
2024	A	`conf`	Recommending Personalised Targeted Training Adjustments for Marathon Runners. RecSys Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
2024	—	`conf`	Reconstructing Children's Faces from Cropped Lip and Nose Images: A Large Mask Inpainting Approach for Privacy-Conscious Cleft Data. MICAD Daniel Anojan Atputharuban, Christoph Theopold, Aonghus Lawlor
2024	J	`jnl`	Rethinking Knee Osteoarthritis Severity Grading: A Few Shot Self-Supervised Contrastive Learning Approach. CoRR Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
2024	—	`conf`	Simulating Real-World News Consumption: Deep Q-Learning for Diverse User-Centric Slate Recommendations. INRA@RecSys Aayush Singha Roy, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley
2024	C	`conf`	Towards Objective Assessment of Cleft Surgical Outcomes: A GAN-Inpainting Based Approach. ICPRAM Daniel Anojan Atputharuban, Christoph Theopold, Aonghus Lawlor
2024	J	`jnl`	Towards a unified approach for unsupervised brain MRI Motion Artefact Detection with few shot Anomaly Detection. Comput. Medical Imaging Graph. Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
2024	—	`conf`	Tracking Lesion Evolution Using a Boundary Enhanced Approach for MS Change Segmentation (BEAMS). LDTM/MMMI/ML4MHD/ML-CDS@MICCAI Prateek Mathur, Brendan S. Kelly, Ronan P. Killeen, Aonghus Lawlor
2024	J	`jnl`	Transformers4NewsRec: A Transformer-based News Recommendation Framework. CoRR Dairui Liu, Honghui Du, Boming Yang, Neil Hurley, Aonghus Lawlor, Irene Li, Derek Greene, Ruihai Dong
2024	—	`conf`	Using Pseudo Cases and Stratified Case-Based Reasoning to Generate and Evaluate Training Adjustments for Marathon Runners. SGAI Conf. (2) Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
2023	C	`conf`	Adaptive Adversarial Samples Based Active Learning for Medical Image Classification. ICPRAM Siteng Ma, Yu An, Jing Wang, Aonghus Lawlor, Ruihai Dong
2023	Misc	`conf`	Addressing Fast Changing Fashion Trends in Multi-Stage Recommender Systems. FLAIRS Aayush Singha Roy, Edoardo D'Amico, Aonghus Lawlor, Neil Hurley
2023	—	`conf`	Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated Cases. ICONIP (15) Haiwen Du, Zheng Ju, Yu An, Honghui Du, Dongjie Zhu, Zhaoshuo Tian, Aonghus Lawlor, Ruihai Dong
2023	J	`jnl`	Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated Cases. CoRR Haiwen Du, Zheng Ju, Yu An, Honghui Du, Dongjie Zhu, Zhaoshuo Tian, Aonghus Lawlor, Ruihai Dong
2023	J	`jnl`	FewSOME: Few Shot Anomaly Detection. CoRR Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
2023	—	`conf`	FewSOME: One-Class Few Shot Anomaly Detection with Siamese Networks. CVPR Workshops Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
2023	—	`conf`	Item Graph Convolution Collaborative Filtering for Inductive Recommendations. ECIR (1) Edoardo D'Amico, Khalil Muhammad, Elias Z. Tragos, Barry Smyth, Neil Hurley, Aonghus Lawlor
2023	J	`jnl`	Item Graph Convolution Collaborative Filtering for Inductive Recommendations. CoRR Edoardo D'Amico, Khalil Muhammad, Elias Z. Tragos, Barry Smyth, Neil Hurley, Aonghus Lawlor
2023	A*	`conf`	Keeping People Active and Healthy at Home Using a Reinforcement Learning-based Fitness Recommendation Framework. IJCAI Elias Z. Tragos, Diarmuid O'Reilly-Morgan, James Geraci, Bichen Shi, Barry Smyth, Cailbhe Doherty, Aonghus Lawlor, Neil Hurley
2023	A	`conf`	Modelling the Training Practices of Recreational Marathon Runners to Make Personalised Training Recommendations. UMAP Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
2023	—	`conf`	Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation. PAKDD (3) Edoardo D'Amico, Aonghus Lawlor, Neil Hurley
2023	J	`jnl`	Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation. CoRR Edoardo D'Amico, Aonghus Lawlor, Neil Hurley
2023	J	`jnl`	RecPrompt: A Prompt Tuning Framework for News Recommendation Using Large Language Models. CoRR Dairui Liu, Boming Yang, Honghui Du, Derek Greene, Aonghus Lawlor, Ruihai Dong, Irene Li
2023	A	`conf`	Scalable Deep Q-Learning for Session-Based Slate Recommendation. RecSys Aayush Singha Roy, Edoardo D'Amico, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley
2022	C	`conf`	An Extended Case-Based Approach to Race-Time Prediction for Recreational Marathon Runners. ICCBR Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
2022	A	`conf`	Entity-Enhanced Graph Convolutional Network for Accurate and Explainable Recommendation. UMAP Qinqin Wang, Elias Z. Tragos, Neil Hurley, Barry Smyth, Aonghus Lawlor, Ruihai Dong
2022	J	`jnl`	Learning Domain-Independent Representations via Shared Weight Auto-Encoder for Transfer Learning in Recommender Systems. IEEE Access Qinqin Wang, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Neil Hurley, Barry Smyth, Aonghus Lawlor, Ruihai Dong
2022	B	`conf`	MARF: User-Item Mutual Aware Representation with Feedback. ICWE Qinqin Wang, Khalil Muhammad, Diarmuid O'Reilly-Morgan, Barry Smyth, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley, Ruihai Dong
2022	J	`jnl`	Recommendations for marathon runners: on the application of recommender systems and machine learning to support recreational marathon runners. User Model. User Adapt. Interact. Barry Smyth, Aonghus Lawlor, Jakim Berndsen, Ciara Feely
2021	C	`conf`	A Case-Based Reasoning Approach to Predicting and Explaining Running Related Injuries. ICCBR Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
2021	—	`conf`	Boosting the Training Time of Weakly Coordinated Distributed Machine Learning. IEEE BigData Erika Duriakova, Elias Z. Tragos, Aonghus Lawlor, Barry Smyth, Neil Hurley
2021	J	`jnl`	DARES: An Asynchronous Distributed Recommender System Using Deep Reinforcement Learning. IEEE Access Bichen Shi, Elias Z. Tragos, Makbule Gulcin Ozsoy, Ruihai Dong, Neil Hurley, Barry Smyth, Aonghus Lawlor
2021	J	`jnl`	Improving Explainable Recommendations by Deep Review-Based Explanations. IEEE Access Sixun Ouyang, Aonghus Lawlor
2021	—	`conf`	Optimising Knee Injury Detection with Spatial Attention and Validating Localisation Ability. MIUA Niamh Belton, Ivan Welaratne, Adil Dahlan, Ronan T. Hearne, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
2021	J	`jnl`	Optimising Knee Injury Detection with Spatial Attention and Validating Localisation Ability. CoRR Niamh Belton, Ivan Welaratne, Adil Dahlan, Ronan T. Hearne, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran
2021	J	`jnl`	Semi-Supervised Siamese Network for Identifying Bad Data in Medical Imaging Datasets. CoRR Niamh Belton, Aonghus Lawlor, Kathleen M. Curran
2020	C	`conf`	A Collaborative Filtering Approach to Successfully Completing The Marathon. ICMLA Jakim Berndsen, Barry Smyth, Aonghus Lawlor
2020	—	`conf`	An Algorithmic Framework for Decentralised Matrix Factorisation. ECML/PKDD (2) Erika Duriakova, Weipéng Huáng, Elias Z. Tragos, Aonghus Lawlor, Barry Smyth, James Geraci, Neil Hurley
2020	A	`conf`	Combining Rating and Review Data by Initializing Latent Factor Models with Topic Models for Top-N Recommendation. RecSys Francisco J. Peña, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Neil Hurley, Erika Duriakova, Barry Smyth, Aonghus Lawlor
2020	A*	`conf`	FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems. KDD Khalil Muhammad, Qinqin Wang, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Barry Smyth, Neil Hurley, James Geraci, Aonghus Lawlor
2020	A	`conf`	Fit to Run: Personalised Recommendations for Marathon Training. RecSys Jakim Berndsen, Barry Smyth, Aonghus Lawlor
2020	J	`jnl`	MP4Rec: Explainable and Accurate Top-N Recommendations in Heterogeneous Information Networks. IEEE Access Makbule Gulcin Ozsoy, Diarmuid O'Reilly-Morgan, Panagiotis Symeonidis, Elias Z. Tragos, Neil Hurley, Barry Smyth, Aonghus Lawlor
2020	—	`conf`	Mining Marathon Training Data to Generate Useful User Profiles. MLSA@PKDD/ECML Jakim Berndsen, Barry Smyth, Aonghus Lawlor
2020	A	`conf`	Providing Explainable Race-Time Predictions and Training Plan Recommendations to Marathon Runners. RecSys Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
2020	C	`conf`	Using Case-Based Reasoning to Predict Marathon Performance and Recommend Tailored Training Plans. ICCBR Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth
2019	—	`conf`	NEAR: A Partner to Explain Any Factorised Recommender System. UMAP (Adjunct Publication) Sixun Ouyang, Aonghus Lawlor
2019	A	`conf`	PDMFRec: a decentralised matrix factorisation with tunable user-centric privacy. RecSys Erika Duriakova, Elias Z. Tragos, Barry Smyth, Neil Hurley, Francisco J. Peña, Panagiotis Symeonidis, James Geraci, Aonghus Lawlor
2019	A	`conf`	Pace my race: recommendations for marathon running. RecSys Jakim Berndsen, Barry Smyth, Aonghus Lawlor
2019	A	`conf`	PyRecGym: a reinforcement learning gym for recommender systems. RecSys Bichen Shi, Makbule Gulcin Ozsoy, Neil Hurley, Barry Smyth, Elias Z. Tragos, James Geraci, Aonghus Lawlor
2019	—	`conf`	UMAP 2019 Workshop on Explainable and Holistic User Modeling (ExHUM) Chairs' Welcome & Organization. UMAP (Adjunct Publication) Cataldo Musto, Amon Rapp, Federica Cena, Frank Hopfgartner, Judy Kay, Aonghus Lawlor, Pasquale Lops, Giovanni Semeraro, Nava Tintarev
2018	Misc	`conf`	A Multi-Domain Analysis of Explanation-Based Recommendation using User-Generated Reviews. FLAIRS Khalil Muhammad, Aonghus Lawlor, Barry Smyth
2018	—	`conf`	Automatic Generation of Natural Language Explanations. IUI Companion Felipe Costa, Sixun Ouyang, Peter Dolog, Aonghus Lawlor
2018	J	`jnl`	Improving Explainable Recommendations with Synthetic Reviews. CoRR Sixun Ouyang, Aonghus Lawlor, Felipe Costa, Peter Dolog
2017	J	`jnl`	Automatic Generation of Natural Language Explanations. CoRR Felipe Costa, Sixun Ouyang, Peter Dolog, Aonghus Lawlor
2017	C	`conf`	On the Pros and Cons of Explanation-Based Ranking. ICCBR Khalil Muhammad, Aonghus Lawlor, Barry Smyth
2017	—	`conf`	Running with Recommendation. HealthRecSys@RecSys Jakim Berndsen, Aonghus Lawlor, Barry Smyth
2016	A	`conf`	A Live-User Study of Opinionated Explanations for Recommender Systems. IUI Khalil Ibrahim Muhammad, Aonghus Lawlor, Barry Smyth
2016	—	`conf`	Explanation-based Ranking in Opinionated Recommender Systems. AICS Khalil Muhammad, Aonghus Lawlor, Barry Smyth
2016	—	`conf`	Exploring Customer Reviews for Music Genre Classification and Evolutionary Studies. ISMIR Sergio Oramas, Luis Espinosa Anke, Aonghus Lawlor, Xavier Serra, Horacio Saggion
2016	Misc	`conf`	On the Use of Opinionated Explanations to Rank and Justify Recommendations. FLAIRS Khalil Muhammad, Aonghus Lawlor, Barry Smyth
2015	—	`conf`	Generating Personalised and Opinionated Review Summaries. UMAP Workshops Khalil Muhammad, Aonghus Lawlor, Rachael Rafter, Barry Smyth
2015	C	`conf`	Great Explanations: Opinionated Explanations for Recommendations. ICCBR Khalil Muhammad, Aonghus Lawlor, Rachael Rafter, Barry Smyth
2015	A	`conf`	News Recommenders: Real-Time, Real-Life Experiences. UMAP Doychin Doychev, Rachael Rafter, Aonghus Lawlor, Barry Smyth
2015	—	`conf`	Opinionated Explanations for Recommendation Systems. SGAI Conf. Aonghus Lawlor, Khalil Muhammad, Rachael Rafter, Barry Smyth
2014	—	`conf`	An Analysis of Recommender Algorithms for Online News. CLEF (Working Notes) Doychin Doychev, Aonghus Lawlor, Rachael Rafter
2014	J	`jnl`	Using Digital Footprints for a City-Scale Traffic Simulation. ACM Trans. Intell. Syst. Technol. Gavin McArdle, Eoghan Furey, Aonghus Lawlor, Alexei Pozdnoukhov
2012	—	`conf`	City-scale traffic simulation from digital footprints. UrbComp@KDD Gavin McArdle, Aonghus Lawlor, Eoghan Furey, Alexei Pozdnoukhov
2009	—	`ch.`	Bootstrap Percolation. Encyclopedia of Complexity and Systems Science Paolo De Gregorio, Aonghus Lawlor, Kenneth A. Dawson
2004	—	`conf`	Cellular Automata with Rare Events; Resolution of an Outstanding Problem in the Bootstrap Percolation Model. ACRI Paolo De Gregorio, Aonghus Lawlor, Phil Bradley, Kenneth A. Dawson