Stochastic Function Norm Regularization of Deep Networks. - Amal Rannen Triki; Matthew B. Blaschko (CoRR, 2016)

Encoder Based Lifelong Learning. - Amal Rannen Triki; Rahaf Aljundi; Matthew B. Blaschko; Tinne Tuytelaars (ICCV, 2017)

Stochastic Weighted Function Norm Regularization. - Amal Rannen Triki; Maxim Berman; Matthew B. Blaschko (CoRR, 2017)

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 (CVPR, 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)

Yes, IoU loss is submodular - as a function of the mispredictions. - Maxim Berman; Matthew B. Blaschko; Amal Rannen Triki; Jiaqian Yu (CoRR, 2018)

A Bayesian Optimization Framework for Neural Network Compression. - Xingchen Ma; Amal Rannen Triki; Maxim Berman; Christos Sagonas; Jacques Calì; Matthew B. Blaschko (ICCV, 2019)

Function Norms for Neural Networks. - Amal Rannen-Triki; Maxim Berman; Vladimir Kolmogorov; Matthew B. Blaschko (ICCV Workshops, 2019)

On the Role of Optimization in Double Descent: A Least Squares Study. - Ilja Kuzborskij; Csaba Szepesvári; Omar Rivasplata; Amal Rannen-Triki; Razvan Pascanu (NeurIPS, 2021)

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 001; Arslan Chaudhry; Xu Owen He; Arthur Douillard; Massimo Caccia; Qixuang Feng; Jiajun Shen; Sylvestre-Alvise Rebuffi; et al. (CoRR, 2022)

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 (NeurIPS, 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)

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)

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 001; Arslan Chaudhry; Xu Owen He; Arthur Douillard; Massimo Caccia; Qixuan Feng; Jiajun Shen; Sylvestre-Alvise Rebuffi; et al. (J. Mach. Learn. Res., 2023)

Kalman Filter for Online Classification of Non-Stationary Data. - Michalis K. Titsias; Alexandre Galashov; Amal Rannen-Triki; Razvan Pascanu; Yee Whye Teh; Jörg Bornschein (ICLR, 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 (NeurIPS, 2024)

Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models. - Amal Rannen-Triki; Jörg Bornschein; Razvan Pascanu; Marcus Hutter; András György 001; Alexandre Galashov; Yee Whye Teh; Michalis K. Titsias (CoRR, 2024)

Transformers for Supervised Online Continual Learning. - Jörg Bornschein; Yazhe Li; Amal Rannen-Triki (CoRR, 2024)