Issam H. Laradji
Issam H. Laradji
Staff Research Scientist at ServiceNow & Adjunct Professor at University of British Columbia
Подтвержден адрес электронной почты в домене servicenow.com - Главная страница
Software defect prediction using ensemble learning on selected features
IH Laradji, M Alshayeb, L Ghouti
Information and Software Technology (IST), 2015
Coordinate descent converges faster with the gauss-southwell rule than random selection
J Nutini, M Schmidt, I Laradji, M Friedlander, H Koepke
International Conference on Machine Learning (ICML), 2015
Where are the blobs: Counting by localization with point supervision
IH Laradji, N Rostamzadeh, PO Pinheiro, D Vazquez, M Schmidt
Proceedings of the European Conference on Computer Vision (ECCV), 2018
Embedding propagation: Smoother manifold for few-shot classification
P Rodríguez, I Laradji, A Drouin, A Lacoste
European Conference on Computer Vision (ECCV), 2020
Painless stochastic gradient: Interpolation, line-search, and convergence rates
S Vaswani, A Mishkin, I Laradji, M Schmidt, G Gidel, S Lacoste-Julien
Neural Information Processing Systems (NeurIPS), 2019
Online fast adaptation and knowledge accumulation: a new approach to continual learning
M Caccia, P Rodriguez, O Ostapenko, F Normandin, M Lin, L Caccia, ...
Neural Information Processing System (NeurIPS), 2020
Stochastic polyak step-size for sgd: An adaptive learning rate for fast convergence
N Loizou, S Vaswani, IH Laradji, S Lacoste-Julien
Artificial Intelligence and Statistics (AISTATS), 2021
A weakly supervised consistency-based learning method for covid-19 segmentation in ct images
I Laradji, P Rodriguez, O Manas, K Lensink, M Law, L Kurzman, W Parker, ...
Winter Conference on Applications of Computer Vision (WACV), 2021
A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis
A Saleh, IH Laradji, DA Konovalov, M Bradley, D Vazquez, M Sheaves
Nature Scientific Reports, 2020
Convergence rates for greedy Kaczmarz algorithms
J Nutini, B Sepehry, A Virani, I Laradji, M Schmidt, H Koepke
Uncertainty in Artificial Intelligence (UAI), 2016
Let's Make Block Coordinate Descent Converge Faster: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence
J Nutini, I Laradji, M Schmidt
Journal of Machine Learning Research (JMLR), 2022
Kubric: A scalable dataset generator
K Greff, F Belletti, L Beyer, C Doersch, Y Du, D Duckworth, DJ Fleet, ...
Computer Vision and Pattern Recognition (CVPR), 2022
Where are the masks: Instance segmentation with image-level supervision
IH Laradji, D Vazquez, M Schmidt
British Machine Vision Conference (BMVC), 2019
M-ADDA: Unsupervised domain adaptation with deep metric learning
IH Laradji, R Babanezhad
Domain Adaptation for Visual Understanding (ICML Workshop), 2020
A survey of self-supervised and few-shot object detection
G Huang, I Laradji, D Vázquez, S Lacoste-Julien, P Rodriguez
Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2022
Proposal-based instance segmentation with point supervision
IH Laradji, N Rostamzadeh, PO Pinheiro, D Vazquez, M Schmidt
International Conference on Image Processing (ICIP), 2020
Beyond trivial counterfactual explanations with diverse valuable explanations
P Rodríguez, M Caccia, A Lacoste, L Zamparo, I Laradji, L Charlin, ...
International Conference on Computer Vision (ICCV), 2021
Cvpr 2020 continual learning in computer vision competition: Approaches, results, current challenges and future directions
V Lomonaco, L Pellegrini, P Rodriguez, M Caccia, Q She, Y Chen, ...
Artificial Intelligence (AI), 2022
Fast and furious convergence: Stochastic second order methods under interpolation
SY Meng, S Vaswani, IH Laradji, M Schmidt, S Lacoste-Julien
Artificial Intelligence and Statistics (AISTATS), 2020
Learning data augmentation with online bilevel optimization for image classification
S Mounsaveng, I Laradji, I Ben Ayed, D Vazquez, M Pedersoli
Winter Conference on Applications of Computer Vision (WACV), 2021
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