Amal Rannen Triki

According to our database, Amal Rannen Triki authored at least 20 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Fine-Tuned In-Context Learners for Efficient Adaptation.

Jörg Bornschein, Clare Lyle, Yazhe Li, Amal Rannen-Triki, Xu Owen He, Razvan Pascanu

CoRR, December, 2025

Benchmarking Diversity in Image Generation via Attribute-Conditional Human Evaluation.

Isabela Albuquerque, Ira Ktena, Olivia Wiles, Ivana Kajic, Amal Rannen-Triki, Cristina Nader Vasconcelos, Aida Nematzadeh

CoRR, November, 2025

2024

Transformers for Supervised Online Continual Learning.

Jörg Bornschein, Yazhe Li, Amal Rannen-Triki

CoRR, 2024

Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models.

Amal Rannen-Triki, Jörg Bornschein, Razvan Pascanu, Marcus Hutter, András György, Alexandre Galashov, Yee Whye Teh, Michalis K. Titsias

CoRR, 2024

Mind the Graph When Balancing Data for Fairness or Robustness.

Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Kalman Filter for Online Classification of Non-Stationary Data.

Michalis K. Titsias, Alexandre Galashov, Amal Rannen-Triki, Razvan Pascanu, Yee Whye Teh, Jörg Bornschein

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research.

Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuan Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato

J. Mach. Learn. Res., 2023

Towards Robust and Efficient Continual Language Learning.

Adam Fisch, Amal Rannen-Triki, Razvan Pascanu, Jörg Bornschein, Angeliki Lazaridou, Elena Gribovskaya, Marc'Aurelio Ranzato

CoRR, 2023

Towards Compute-Optimal Transfer Learning.

Massimo Caccia, Alexandre Galashov, Arthur Douillard, Amal Rannen-Triki, Dushyant Rao, Michela Paganini, Laurent Charlin, Marc'Aurelio Ranzato, Razvan Pascanu

CoRR, 2023

Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union.

Zifu Wang, Maxim Berman, Amal Rannen-Triki, Philip H. S. Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research.

Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuang Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato

CoRR, 2022

2021

On the Role of Optimization in Double Descent: A Least Squares Study.

Ilja Kuzborskij, Csaba Szepesvári, Omar Rivasplata, Amal Rannen-Triki, Razvan Pascanu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2019

Function Norms for Neural Networks.

Amal Rannen-Triki, Maxim Berman, Vladimir Kolmogorov, Matthew B. Blaschko

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

A Bayesian Optimization Framework for Neural Network Compression.

Xingchen Ma, Amal Rannen Triki, Maxim Berman, Christos Sagonas, Jacques Calì, Matthew B. Blaschko

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Yes, IoU loss is submodular - as a function of the mispredictions.

Maxim Berman, Matthew B. Blaschko, Amal Rannen Triki, Jiaqian Yu

CoRR, 2018

Intraoperative margin assessment of human breast tissue in optical coherence tomography images using deep neural networks.

Amal Rannen Triki, Matthew B. Blaschko, Yoon Mo Jung, Seungri Song, Hyun Ju Han, Seung Il Kim, Chulmin Joo

Comput. Medical Imaging Graph., 2018

The Lovász-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks.

Maxim Berman, Amal Rannen Triki, Matthew B. Blaschko

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Stochastic Weighted Function Norm Regularization.

Amal Rannen Triki, Maxim Berman, Matthew B. Blaschko

CoRR, 2017

Encoder Based Lifelong Learning.

Amal Rannen Triki, Rahaf Aljundi, Matthew B. Blaschko, Tinne Tuytelaars

Proceedings of the IEEE International Conference on Computer Vision, 2017

2016

Stochastic Function Norm Regularization of Deep Networks.

Amal Rannen Triki, Matthew B. Blaschko

CoRR, 2016