Paul Albert

Postodoctoral Reseacher at in Australian Institute for Machine Learning @TheAIML

[Paul Albert @PaulAlbert31]

New paper at ICLR 25 !
https://t.co/kkHO2yLmvQ
https://t.co/HadQ8ayMaU

We evidence the low-rank bottleneck of LoRA, showing that scaling trainable parameters isn't always enough.
Plus, RandLoRA optimizes gradient computation to reduce memory use over LoRA !
#peft #ICLR2025

[Paul Albert @PaulAlbert31]

@TheAIML Co-authors: Dr. @fredzzhang Dr. Hemanth Saratachandran Dr. Cristian Rodriguez-Opazo Dr. Ehsan Abbasnejad and Prof @AntonvdH

[Paul Albert @PaulAlbert31]

New paper at ICLR 25 !
https://t.co/kkHO2yLmvQ
https://t.co/HadQ8ayMaU

We evidence the low-rank bottleneck of LoRA, showing that scaling trainable parameters isn't always enough.
Plus, RandLoRA optimizes gradient computation to reduce memory use over LoRA !
#peft #ICLR2025

[Paul Albert @PaulAlbert31]

This research was conducted in collaboration with co-authors at @TheAIML under the CAR program. We invite you to explore the paper and accompanying codebase: https://t.co/GVUyVSjkET

[Paul Albert @PaulAlbert31]

Check out our new work freshly accepted at #neurips2024 where we improve knowledge composition and few-shot generalization in large transformer models using learnt anisotropic scaling of task vectors. Paper: https://t.co/WNkKTBd5fR Code: https://t.co/9iafSTktWf

[Frederic Zhang @fredzzhang]

Excited to announce that the codebase for our #neurips2024 paper Knowledge Composition using Task Vectors with Learned Anisotropic Scaling (https://t.co/yCekofQ6xq) is now available. In this paper, we showed how to combine or transfer the knowledge across different models. [1/6]

[Frederic Zhang @fredzzhang]

Excited to announce that the codebase for our #neurips2024 paper Knowledge Composition using Task Vectors with Learned Anisotropic Scaling (https://t.co/yCekofQ6xq) is now available. In this paper, we showed how to combine or transfer the knowledge across different models. [1/6]

[Paul Albert @PaulAlbert31]

Co-authors: @jvlmdr @ArazoEric @tkrishnna @oconnorn

[Paul Albert @PaulAlbert31]

#ECCV2024 is on !
Check out our work on learning from noisy datasets where we observe that detecting out-of-distribution training images using unsupervised learning discards highly important clean examples and how to recover them.
@insight_centre @TheAIML
https://t.co/95bL7JnnrG

[Prof. Noel O'Connor (he/him) @oconnorn]

Congrats to @PaulAlbert31 who successfully defended his PhD thesis "Deep Learning for Computer Vision constrained by Limited Supervision". Jointly-supervised with @kevinmcguinness. Thanks to examiners @fosterjendublin & Prof Yannis Patras of @QMEECS @VistaMilk @insight_centre

[Paul Albert @PaulAlbert31]

Our label noise robust algorithm PLS detects incorrect true label guesses using our pseudo-loss to combat label noise in image classification datasets
https://t.co/AKPLgGEcz4.
Co-authors:
@ArazoEric
@tkrishnna
@oconnorn
@kevinmcguinness

[Paul Albert @PaulAlbert31]

The end of a great poster session at #WACV2023 in sunny Waikoloa Hawaii !
I presented PLS my latest label noise paper . This is the result of a great ongoing collaboration with the support of @VistaMilk and @insight_centre. Co-authors 👇

[VistaMilk Research Ireland Centre @VistaMilk]

Congratulations to our researchers Paul Albert and Hannah Masterson on winning awards for best oral presentation at the VistaMilk industry day 👏 @scienceirel @agriculture_ie

[Paul Albert @PaulAlbert31]

The code for our latest label noise paper PLS https://t.co/AKPLgGVNqC was just released on github https://t.co/3ymz6K0u97. Feel free to reproduce our results and test on your own noisy dataset ! Team: @ArazoEric @tkrishnna @oconnorn @kevinmcguinness

[Paul Albert @PaulAlbert31]

Just out of an intense poster session #ECCV2022 on Tel Aviv. We detect two forms of label noise using unsupervised contrastive leaning. Paper: https://t.co/SMJhXQqPX4.
A fruitful collaboration between @insight_centre and @VistaMilk funded by @scienceirel

[Paul Albert @PaulAlbert31]

I just presented my latest work on computer vision in the presence of label noise to the Insight Smart Surrounding showcase #InsightSSS22 @DCU. A research collaboration between by @VistaMilk and @insight_centre @scienceirel. Great to see everyone in person !

[Paul Albert @PaulAlbert31]

Our paper: "Is your noise correction noisy?
PLS: Robustness to label noise with two stage detection" was accepted at #WACV2023 ! We detect incorrect true label guesses using our pseudo-loss to combat label noise in image classification datasets
https://t.co/AKPLgGEKoC