Aonghus Lawlor

Orcid: 0000-0002-6160-4639

According to our database1, Aonghus Lawlor authored at least 58 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Breaking the Barrier: Selective Uncertainty-based Active Learning for Medical Image Segmentation.
CoRR, 2024

Enhancing Surgical Visualization: Feasibility Study on GAN-Based Image Generation for Post Operative Cleft Palate Images.
Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods, 2024

A Hybrid Decentralised Learning Topology for Recommendations with Improved Privacy.
Proceedings of the 4th Workshop on Machine Learning and Systems, 2024

ALS Algorithm for Robust and Communication-Efficient Federated Learning.
Proceedings of the 4th Workshop on Machine Learning and Systems, 2024

2023
RecPrompt: A Prompt Tuning Framework for News Recommendation Using Large Language Models.
CoRR, 2023

FewSOME: Few Shot Anomaly Detection.
CoRR, 2023

Modelling the Training Practices of Recreational Marathon Runners to Make Personalised Training Recommendations.
Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, 2023

Scalable Deep Q-Learning for Session-Based Slate Recommendation.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Keeping People Active and Healthy at Home Using a Reinforcement Learning-based Fitness Recommendation Framework.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Adaptive Adversarial Samples Based Active Learning for Medical Image Classification.
Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods, 2023

Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated Cases.
Proceedings of the Neural Information Processing - 30th International Conference, 2023

Addressing Fast Changing Fashion Trends in Multi-Stage Recommender Systems.
Proceedings of the Thirty-Sixth International Florida Artificial Intelligence Research Society Conference, 2023

Item Graph Convolution Collaborative Filtering for Inductive Recommendations.
Proceedings of the Advances in Information Retrieval, 2023

FewSOME: One-Class Few Shot Anomaly Detection with Siamese Networks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Recommendations for marathon runners: on the application of recommender systems and machine learning to support recreational marathon runners.
User Model. User Adapt. Interact., 2022

Learning Domain-Independent Representations via Shared Weight Auto-Encoder for Transfer Learning in Recommender Systems.
IEEE Access, 2022

Entity-Enhanced Graph Convolutional Network for Accurate and Explainable Recommendation.
Proceedings of the UMAP '22: 30th ACM Conference on User Modeling, Adaptation and Personalization, Barcelona, Spain, July 4, 2022

MARF: User-Item Mutual Aware Representation with Feedback.
Proceedings of the Web Engineering - 22nd International Conference, 2022

An Extended Case-Based Approach to Race-Time Prediction for Recreational Marathon Runners.
Proceedings of the Case-Based Reasoning Research and Development, 2022

2021
Semi-Supervised Siamese Network for Identifying Bad Data in Medical Imaging Datasets.
CoRR, 2021

DARES: An Asynchronous Distributed Recommender System Using Deep Reinforcement Learning.
IEEE Access, 2021

Improving Explainable Recommendations by Deep Review-Based Explanations.
IEEE Access, 2021

Optimising Knee Injury Detection with Spatial Attention and Validating Localisation Ability.
Proceedings of the Medical Image Understanding and Analysis - 25th Annual Conference, 2021

A Case-Based Reasoning Approach to Predicting and Explaining Running Related Injuries.
Proceedings of the Case-Based Reasoning Research and Development, 2021

Boosting the Training Time of Weakly Coordinated Distributed Machine Learning.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
MP4Rec: Explainable and Accurate Top-N Recommendations in Heterogeneous Information Networks.
IEEE Access, 2020

Combining Rating and Review Data by Initializing Latent Factor Models with Topic Models for Top-N Recommendation.
Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

Providing Explainable Race-Time Predictions and Training Plan Recommendations to Marathon Runners.
Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

Fit to Run: Personalised Recommendations for Marathon Training.
Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

An Algorithmic Framework for Decentralised Matrix Factorisation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Mining Marathon Training Data to Generate Useful User Profiles.
Proceedings of the Machine Learning and Data Mining for Sports Analytics, 2020

FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

A Collaborative Filtering Approach to Successfully Completing The Marathon.
Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

Using Case-Based Reasoning to Predict Marathon Performance and Recommend Tailored Training Plans.
Proceedings of the Case-Based Reasoning Research and Development, 2020

2019
NEAR: A Partner to Explain Any Factorised Recommender System.
Proceedings of the Adjunct Publication of the 27th Conference on User Modeling, 2019

UMAP 2019 Workshop on Explainable and Holistic User Modeling (ExHUM) Chairs' Welcome & Organization.
Proceedings of the Adjunct Publication of the 27th Conference on User Modeling, 2019

PyRecGym: a reinforcement learning gym for recommender systems.
Proceedings of the 13th ACM Conference on Recommender Systems, 2019

PDMFRec: a decentralised matrix factorisation with tunable user-centric privacy.
Proceedings of the 13th ACM Conference on Recommender Systems, 2019

Pace my race: recommendations for marathon running.
Proceedings of the 13th ACM Conference on Recommender Systems, 2019

2018
Improving Explainable Recommendations with Synthetic Reviews.
CoRR, 2018

Automatic Generation of Natural Language Explanations.
Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion, 2018

A Multi-Domain Analysis of Explanation-Based Recommendation using User-Generated Reviews.
Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

2017
Running with Recommendation.
Proceedings of the 2nd International Workshop on Health Recommender Systems co-located with the 11th International Conference on Recommender Systems (RecSys 2017), 2017

On the Pros and Cons of Explanation-Based Ranking.
Proceedings of the Case-Based Reasoning Research and Development, 2017

2016
A Live-User Study of Opinionated Explanations for Recommender Systems.
Proceedings of the 21st International Conference on Intelligent User Interfaces, 2016

Exploring Customer Reviews for Music Genre Classification and Evolutionary Studies.
Proceedings of the 17th International Society for Music Information Retrieval Conference, 2016

On the Use of Opinionated Explanations to Rank and Justify Recommendations.
Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, 2016

Explanation-based Ranking in Opinionated Recommender Systems.
Proceedings of the 24th Irish Conference on Artificial Intelligence and Cognitive Science, 2016

2015
Generating Personalised and Opinionated Review Summaries.
Proceedings of the Posters, Demos, Late-breaking Results and Workshop Proceedings of the 23rd Conference on User Modeling, Adaptation, and Personalization (UMAP 2015), Dublin, Ireland, June 29, 2015

News Recommenders: Real-Time, Real-Life Experiences.
Proceedings of the User Modeling, Adaptation and Personalization, 2015

Opinionated Explanations for Recommendation Systems.
Proceedings of the Research and Development in Intelligent Systems XXXII, 2015

Great Explanations: Opinionated Explanations for Recommendations.
Proceedings of the Case-Based Reasoning Research and Development, 2015

2014
Using Digital Footprints for a City-Scale Traffic Simulation.
ACM Trans. Intell. Syst. Technol., 2014

An Analysis of Recommender Algorithms for Online News.
Proceedings of the Working Notes for CLEF 2014 Conference, 2014

2012
City-scale traffic simulation from digital footprints.
Proceedings of the ACM SIGKDD International Workshop on Urban Computing, 2012

2009
Bootstrap Percolation.
Proceedings of the Encyclopedia of Complexity and Systems Science, 2009

2004
Cellular Automata with Rare Events; Resolution of an Outstanding Problem in the Bootstrap Percolation Model.
Proceedings of the Cellular Automata, 2004


  Loading...