Paul Albert

40 papers A* 5A 5B 3Journal 20Unranked 7
YearRankTypeTitle / Venue / Authors
2026 A* conf
SineLoRA∆: Sine-Activated Delta Compression.
AAAI
Cameron Gordon, Yiping Ji, Hemanth Saratchandran, Paul Albert, Simon Lucey
2025 J jnl
Compressing Sine-Activated Low-Rank Adapters through Post-Training Quantization.
CoRR
Cameron Gordon, Yiping Ji, Hemanth Saratchandran, Paul Albert, Simon Lucey
2025 A conf
In-context Learning for Addressing User Cold-start in Sequential Movie Recommenders.
RecSys
Xurong Liang, Vu Nguyen, Vuong Le, Paul Albert, Julien Monteil
2025 A* conf
RandLoRA: Full rank parameter-efficient fine-tuning of large models.
ICLR
Paul Albert, Frederic Z. Zhang, Hemanth Saratchandran, Cristian Rodriguez Opazo, Anton van den Hengel, Ehsan Abbasnejad
2025 J jnl
RandLoRA: Full-rank parameter-efficient fine-tuning of large models.
CoRR
Paul Albert, Frederic Z. Zhang, Hemanth Saratchandran, Cristian Rodriguez Opazo, Anton van den Hengel, Ehsan Abbasnejad
2025 J jnl
Towards Higher Effective Rank in Parameter-efficient Fine-tuning using Khatri-Rao Product.
CoRR
Paul Albert, Frederic Z. Zhang, Hemanth Saratchandran, Anton van den Hengel, Ehsan Abbasnejad
2024 — conf
An Accurate Detection Is Not All You Need to Combat Label Noise in Web-Noisy Datasets.
ECCV (49)
Paul Albert, Jack Valmadre, Eric Arazo, Tarun Krishna, Noel E. O'Connor, Kevin McGuinness
2024 J jnl
An accurate detection is not all you need to combat label noise in web-noisy datasets.
CoRR
Paul Albert, Jack Valmadre, Eric Arazo, Tarun Krishna, Noel E. O'Connor, Kevin McGuinness
2024 — conf
Energy-Efficient Uncertainty-Aware Biomass Composition Prediction at the Edge.
CVPR Workshops
Muhammad Zawish, Paul Albert, Flavio Esposito, Steven Davy, Lizy Abraham
2024 J jnl
Energy-Efficient Uncertainty-Aware Biomass Composition Prediction at the Edge.
CoRR
Muhammad Zawish, Paul Albert, Flavio Esposito, Steven Davy, Lizy Abraham
2024 A* conf
Knowledge Composition using Task Vectors with Learned Anisotropic Scaling.
NeurIPS
Frederic Z. Zhang, Paul Albert, Cristian Rodriguez Opazo, Anton van den Hengel, Ehsan Abbasnejad
2024 J jnl
Knowledge Composition using Task Vectors with Learned Anisotropic Scaling.
CoRR
Frederic Z. Zhang, Paul Albert, Cristian Rodriguez Opazo, Anton van den Hengel, Ehsan Abbasnejad
2023 A conf
Is your noise correction noisy? PLS: Robustness to label noise with two stage detection.
WACV
Paul Albert, Eric Arazo, Tarun Krishna, Noel E. O'Connor, Kevin McGuinness
2023 A conf
Unifying Synergies between Self-supervised Learning and Dynamic Computation.
BMVC
Tarun Krishna, Ayush K. Rai, Alexandru Drimbarean, Eric Arazo, Paul Albert, Alan F. Smeaton, Kevin McGuinness, Noel E. O'Connor
2022 A conf
Addressing out-of-distribution label noise in webly-labelled data.
WACV
Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness
2022 — conf
Embedding Contrastive Unsupervised Features to Cluster In- And Out-of-Distribution Noise in Corrupted Image Datasets.
ECCV (31)
Paul Albert, Eric Arazo, Noel E. O'Connor, Kevin McGuinness
2022 J jnl
Embedding contrastive unsupervised features to cluster in- and out-of-distribution noise in corrupted image datasets.
CoRR
Paul Albert, Eric Arazo, Noel E. O'Connor, Kevin McGuinness
2022 J jnl
Is your noise correction noisy? PLS: Robustness to label noise with two stage detection.
CoRR
Paul Albert, Eric Arazo, Tarun Krishna, Noel E. O'Connor, Kevin McGuinness
2022 — conf
Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation.
CVPR Workshops
Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Noel E. O'Connor, Kevin McGuinness
2022 J jnl
Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation.
CoRR
Paul Albert, Mohamed Saadeldin, Badri Narayanan, Jaime B. Fernandez, Brian Mac Namee, Deirdre Hennessy, Noel E. O'Connor, Kevin McGuinness
2022 J jnl
Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation.
CoRR
Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling H. O'Connor, Noel E. O'Connor, Kevin McGuinness
2021 — conf
Adaptation of Compositional Data Analysis in Deep Learning to Predict Pasture Biomass Proportions.
AICS
Badri Narayanan, Mohamed Saadeldin, Paul Albert, Kevin McGuinness, Noel E. O'Connor, Brian Mac Namee
2021 J jnl
Addressing out-of-distribution label noise in webly-labelled data.
CoRR
Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness
2021 J jnl
Extracting Pasture Phenotype and Biomass Percentages using Weakly Supervised Multi-target Deep Learning on a Small Dataset.
CoRR
Badri Narayanan, Mohamed Saadeldin, Paul Albert, Kevin McGuinness, Brian Mac Namee
2021 A conf
How Important is Importance Sampling for Deep Budgeted Training?
BMVC
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
2021 J jnl
How Important is Importance Sampling for Deep Budgeted Training?
CoRR
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
2021 A* conf
Multi-Objective Interpolation Training for Robustness To Label Noise.
CVPR
Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness
2021 B conf
ReLaB: Reliable Label Bootstrapping for Semi-Supervised Learning.
IJCNN
Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness
2021 — conf
Semi-supervised dry herbage mass estimation using automatic data and synthetic images.
ICCVW
Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling O'Connor, Noel E. O'Connor, Kevin McGuinness
2021 J jnl
Semi-supervised dry herbage mass estimation using automatic data and synthetic images.
CoRR
Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling O'Connor, Noel E. O'Connor, Kevin McGuinness
2020 J jnl
Multi-Objective Interpolation Training for Robustness to Label Noise.
CoRR
Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness
2020 B conf
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning.
IJCNN
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
2020 J jnl
ReLaB: Reliable Label Bootstrapping for Semi-Supervised Learning.
CoRR
Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness
2020 B conf
Towards Robust Learning with Different Label Noise Distributions.
ICPR
Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness
2019 J jnl
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning.
CoRR
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
2019 J jnl
Towards Robust Learning with Different Label Noise Distributions.
CoRR
Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness
2019 A* conf
Unsupervised Label Noise Modeling and Loss Correction.
ICML
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
2019 J jnl
Unsupervised label noise modeling and loss correction.
CoRR
Eric Arazo Sanchez, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
2012 — conf
Research discovery through linked open data.
JCDL
Paul Albert, Kristi L. Holmes, Katy Börner, Mike Conlon
1999 J jnl
The efficacy of matching information systems development methodologies with application characteristics - an empirical study.
J. Syst. Softw.
Geoffry S. Howard, Thomas Bodnovich, Thomas Janicki, Jens Liegle, Steven Klein, Paul Albert, David Cannon