Följ
Issam H. Laradji
Issam H. Laradji
Staff Research Scientist at ServiceNow & Adjunct Professor at University of British Columbia
Verifierad e-postadress på servicenow.com - Startsida
Titel
Citeras av
Citeras av
År
Software defect prediction using ensemble learning on selected features
IH Laradji, M Alshayeb, L Ghouti
Information and Software Technology (IST), 2015
4952015
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
2752015
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
2482019
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
2472018
Embedding propagation: Smoother manifold for few-shot classification
P Rodríguez, I Laradji, A Drouin, A Lacoste
European Conference on Computer Vision (ECCV), 2020
2402020
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
2152022
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
2072021
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
163*2020
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
1452020
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
1042022
Data Augmentation for Intent Classification with Off-the-shelf Large Language Models
G Sahu, P Rodriguez, IH Laradji, P Atighehchian, D Vazquez, ...
NLP4ConvAI 2022, 2022
1042022
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
1042021
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
98*2022
Convergence rates for greedy Kaczmarz algorithms
J Nutini, B Sepehry, A Virani, I Laradji, M Schmidt, H Koepke
Uncertainty in Artificial Intelligence (UAI), 2016
86*2016
Where are the masks: Instance segmentation with image-level supervision
IH Laradji, D Vazquez, M Schmidt
British Machine Vision Conference (BMVC), 2019
702019
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
652021
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
622022
Proposal-based instance segmentation with point supervision
IH Laradji, N Rostamzadeh, PO Pinheiro, D Vazquez, M Schmidt
International Conference on Image Processing (ICIP), 2020
59*2020
M-ADDA: Unsupervised domain adaptation with deep metric learning
IH Laradji, R Babanezhad
Domain Adaptation for Visual Understanding (ICML Workshop), 2020
592020
Neural point light fields
J Ost, I Laradji, A Newell, Y Bahat, F Heide
Conference on Computer Vision and Pattern Recognition (CVPR), 2022
522022
Systemet kan inte utföra åtgärden just nu. Försök igen senare.
Artiklar 1–20