Issam H. Laradji

According to our database, Issam H. Laradji authored at least 66 papers between 2013 and 2024.

Collaborative distances:

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

2024

MixSumm: Topic-based Data Augmentation using LLMs for Low-resource Extractive Text Summarization.

Gaurav Sahu, Issam H. Laradji

CoRR, 2024

InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation.

Gaurav Sahu, Abhay Puri, Juan A. Rodriguez, Alexandre Drouin, Perouz Taslakian, Valentina Zantedeschi, Alexandre Lacoste, David Vázquez, Nicolas Chapados, Christopher Pal, Sai Rajeswar, Issam Hadj Laradji

CoRR, 2024

BlockLLM: Memory-Efficient Adaptation of LLMs by Selecting and Optimizing the Right Coordinate Blocks.

Amrutha Varshini Ramesh, Vignesh Ganapathiraman, Issam H. Laradji, Mark Schmidt

CoRR, 2024

WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?

Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, Léo Boisvert, Megh Thakkar, Quentin Cappart, David Vázquez, Nicolas Chapados, Alexandre Lacoste

CoRR, 2024

LitLLM: A Toolkit for Scientific Literature Review.

Shubham Agarwal, Issam H. Laradji, Laurent Charlin, Christopher Pal

CoRR, 2024

WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?

Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, David Vázquez, Nicolas Chapados, Alexandre Lacoste

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

A Survey of Self-Supervised and Few-Shot Object Detection.

Gabriel Huang, Issam H. Laradji, David Vázquez, Simon Lacoste-Julien, Pau Rodríguez

IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Explaining Visual Counterfactual Explainers.

Diego A. Velázquez, Pau Rodríguez, Alexandre Lacoste, Issam H. Laradji, F. Xavier Roca, Jordi Gonzàlez

Trans. Mach. Learn. Res., 2023

Workflow Discovery from Dialogues in the Low Data Regime.

Amine El Hattami, Issam H. Laradji, Stefania Raimondo, David Vázquez, Pau Rodríguez, Christopher Pal

Trans. Mach. Learn. Res., 2023

Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants via the Mirror Stochastic Polyak Stepsize.

Ryan D'Orazio, Nicolas Loizou, Issam H. Laradji, Ioannis Mitliagkas

Trans. Mach. Learn. Res., 2023

Capture the Flag: Uncovering Data Insights with Large Language Models.

Issam H. Laradji, Perouz Taslakian, Sai Rajeswar, Valentina Zantedeschi, Alexandre Lacoste, Nicolas Chapados, David Vázquez, Christopher Pal, Alexandre Drouin

CoRR, 2023

StarVector: Generating Scalable Vector Graphics Code from Images.

Juan A. Rodriguez, Shubham Agarwal, Issam H. Laradji, Pau Rodríguez, David Vázquez, Christopher Pal, Marco Pedersoli

CoRR, 2023

LLM aided semi-supervision for Extractive Dialog Summarization.

Nishant Mishra, Gaurav Sahu, Iacer Calixto, Ameen Abu-Hanna, Issam H. Laradji

CoRR, 2023

Enchancing Semi-Supervised Learning for Extractive Summarization with an LLM-based pseudolabeler.

Gaurav Sahu, Olga Vechtomova, Issam H. Laradji

CoRR, 2023

Automatic Data Augmentation Learning using Bilevel Optimization for Histopathological Images.

Saypraseuth Mounsaveng, Issam H. Laradji, David Vázquez, Marco Pedersoli, Ismail Ben Ayed

CoRR, 2023

Long-Context Language Decision Transformers and Exponential Tilt for Interactive Text Environments.

Nicolas Gontier, Pau Rodríguez, Issam H. Laradji, David Vázquez, Christopher Pal

CoRR, 2023

OCR-VQGAN: Taming Text-within-Image Generation.

Juan A. Rodriguez, David Vázquez, Issam H. Laradji, Marco Pedersoli, Pau Rodríguez

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

FigGen: Text to Scientific Figure Generation.

Juan A. Rodriguez, David Vázquez, Issam H. Laradji, Marco Pedersoli, Pau Rodríguez

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Constraining Representations Yields Models That Know What They Don't Know.

João Monteiro, Pau Rodríguez, Pierre-André Noël, Issam H. Laradji, David Vázquez

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Affinity Learning With Blind-Spot Self-Supervision for Image Denoising.

Yuhongze Zhou, Liguang Zhou, Issam Hadj Laradji, Tin Lun Lam, Yangsheng Xu

Proceedings of the IEEE International Conference on Acoustics, 2023

PromptMix: A Class Boundary Augmentation Method for Large Language Model Distillation.

Gaurav Sahu, Olga Vechtomova, Dzmitry Bahdanau, Issam H. Laradji

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

LLM aided semi-supervision for efficient Extractive Dialog Summarization.

Nishant Mishra, Gaurav Sahu, Iacer Calixto, Ameen Abu-Hanna, Issam H. Laradji

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

Let's Make Block Coordinate Descent Converge Faster: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence.

Julie Nutini, Issam H. Laradji, Mark Schmidt

J. Mach. Learn. Res., 2022

Challenges in leveraging GANs for few-shot data augmentation.

Christopher Beckham, Issam H. Laradji, Pau Rodríguez, David Vázquez, Derek Nowrouzezahrai, Christopher J. Pal

CoRR, 2022

CVPR 2020 continual learning in computer vision competition: Approaches, results, current challenges and future directions.

Vincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodríguez, Massimo Caccia, Qi She, Yu Chen, Quentin Jodelet, Ruiping Wang, Zheda Mai, David Vázquez, German Ignacio Parisi, Nikhil Churamani, Marc Pickett, Issam H. Laradji, Davide Maltoni

Artif. Intell., 2022

Kubric: A scalable dataset generator.

Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, A. Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Overcoming challenges in leveraging GANs for few-shot data augmentation.

Christopher Beckham, Issam H. Laradji, Pau Rodríguez, David Vázquez, Derek Nowrouzezahrai, Christopher Pal

Proceedings of the Conference on Lifelong Learning Agents, 2022

OSM: An Open Set Matting Framework with OOD Detection and Few-Shot Learning.

Yuhongze Zhou, Issam Hadj Laradji, Liguang Zhou, Derek Nowrouzezahrai

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

Consistency-CAM: Towards Improved Weakly Supervised Semantic Segmentation.

Sai Rajeswar, Issam Hadj Laradji, Pau Rodríguez, David Vázquez, Aaron C. Courville

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

Data Augmentation for Intent Classification with Off-the-shelf Large Language Models.

Gaurav Sahu, Pau Rodríguez, Issam H. Laradji, Parmida Atighehchian, David Vázquez, Dzmitry Bahdanau

Proceedings of the 4th Workshop on NLP for Conversational AI, 2022

2021

A Deep Learning Localization Method for Measuring Abdominal Muscle Dimensions in Ultrasound Images.

Alzayat Saleh, Issam H. Laradji, Corey Lammie, David Vázquez, Carol A. Flavell, Mostafa Rahimi Azghadi

IEEE J. Biomed. Health Informatics, 2021

Learning Data Augmentation with Online Bilevel Optimization for Image Classification.

Saypraseuth Mounsaveng, Issam H. Laradji, Ismail Ben Ayed, David Vázquez, Marco Pedersoli

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images.

Issam H. Laradji, Pau Rodríguez, Oscar Mañas, Keegan Lensink, Marco Law, Lironne Kurzman, William Parker, David Vázquez, Derek Nowrouzezahrai

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction.

Issam H. Laradji, Pau Rodríguez, David Vázquez, Derek Nowrouzezahrai

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations.

Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vázquez

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence.

Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery.

Issam H. Laradji, Pau Rodríguez, Freddie Kalaitzis, David Vázquez, Ross Young, Ed Davey, Alexandre Lacoste

CoRR, 2020

Affinity LCFCN: Learning to Segment Fish with Weak Supervision.

Issam H. Laradji, Alzayat Saleh, Pau Rodríguez, Derek Nowrouzezahrai, Mostafa Rahimi Azghadi, David Vázquez

CoRR, 2020

A Realistic Fish-Habitat Dataset to Evaluate Algorithms for Underwater Visual Analysis.

Alzayat Saleh, Issam H. Laradji, Dmitry A. Konovalov, Michael Bradley, David Vázquez, Marcus Sheaves

CoRR, 2020

A Weakly Supervised Region-Based Active Learning Method for COVID-19 Segmentation in CT Images.

Issam H. Laradji, Pau Rodríguez, Frederic Branchaud-Charron, Keegan Lensink, Parmida Atighehchian, William Parker, David Vázquez, Derek Nowrouzezahrai

CoRR, 2020

Segmentation of Pulmonary Opacification in Chest CT Scans of COVID-19 Patients.

Keegan Lensink, Issam H. Laradji, Marco Law, Paolo Emilio Barbano, Savvas Nicolaou, William Parker, Eldad Haber

CoRR, 2020

Adaptive Gradient Methods Converge Faster with Over-Parameterization (and you can do a line-search).

Sharan Vaswani, Frederik Kunstner, Issam H. Laradji, Si Yi Meng, Mark Schmidt, Simon Lacoste-Julien

CoRR, 2020

Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning.

Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin

CoRR, 2020

Synbols: Probing Learning Algorithms with Synthetic Datasets.

Alexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning.

Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Proposal-Based Instance Segmentation With Point Supervision.

Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro, David Vázquez, Mark Schmidt

Proceedings of the IEEE International Conference on Image Processing, 2020

Looc: Localize Overlapping Objects with Count Supervision.

Issam H. Laradji, Rafael Pardinas, Pau Rodríguez, David Vázquez

Proceedings of the IEEE International Conference on Image Processing, 2020

Embedding Propagation: Smoother Manifold for Few-Shot Classification.

Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste

Proceedings of the Computer Vision - ECCV 2020, 2020

Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation.

Si Yi Meng, Sharan Vaswani, Issam Hadj Laradji, Mark Schmidt, Simon Lacoste-Julien

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning.

Issam H. Laradji, Reza Babanezhad

Proceedings of the Domain Adaptation for Visual Understanding, 2020

2019

Instance Segmentation with Point Supervision.

Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro, David Vázquez, Mark Schmidt

CoRR, 2019

Efficient Deep Gaussian Process Models for Variable-Sized Input.

Issam H. Laradji, Mark Schmidt, Vladimir Pavlovic, Minyoung Kim

CoRR, 2019

Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates.

Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient Deep Gaussian Process Models for Variable-Sized Inputs.

Issam H. Laradji, Mark Schmidt, Vladimir Pavlovic, Minyoung Kim

Proceedings of the International Joint Conference on Neural Networks, 2019

Class-Based Styling: Real-Time Localized Style Transfer with Semantic Segmentation.

Lironne Kurzman, David Vázquez, Issam H. Laradji

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

Where are the Masks: Instance Segmentation with Image-level Supervision.

Issam H. Laradji, David Vázquez, Mark Schmidt

Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018

M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning.

Issam H. Laradji, Reza Babanezhad

CoRR, 2018

MASAGA: A Linearly-Convergent Stochastic First-Order Method for Optimization on Manifolds.

Reza Babanezhad, Issam H. Laradji, Alireza Shafaei, Mark Schmidt

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Where Are the Blobs: Counting by Localization with Point Supervision.

Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro, David Vázquez, Mark Schmidt

Proceedings of the Computer Vision - ECCV 2018, 2018

2016

Convergence Rates for Greedy Kaczmarz Algorithms, and Faster Randomized Kaczmarz Rules Using the Orthogonality Graph.

Julie Nutini, Behrooz Sepehry, Issam H. Laradji, Mark Schmidt, Hoyt A. Koepke, Alim Virani

CoRR, 2016

Convergence Rates for Greedy Kaczmarz Algorithms, and Randomized Kaczmarz Rules Using the Orthogonality Graph.

Julie Nutini, Behrooz Sepehry, Issam H. Laradji, Mark Schmidt, Hoyt A. Koepke, Alim Virani

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

2015

Software defect prediction using ensemble learning on selected features.

Issam H. Laradji, Mohammad R. Alshayeb, Lahouari Ghouti

Inf. Softw. Technol., 2015

Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection.

Julie Nutini, Mark Schmidt, Issam H. Laradji, Michael P. Friedlander, Hoyt A. Koepke

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Sparse Single-Hidden Layer Feedforward Network for Mapping Natural Language Questions to SQL Queries.

Issam H. Laradji, Lahouari Ghouti, Faisal Saleh, Musab A. AlTurki

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

XML classification using ensemble learning on extracted features.

Issam H. Laradji, Salahadin Mohammed, Lahouari Ghouti

Proceedings of the 2014 ACM Southeast Regional Conference, Kennesaw, GA, USA, March 28, 2014

2013

Perceptual hashing of color images using hypercomplex representations.

Issam H. Laradji, Lahouari Ghouti, El-Hebri Khiari

Proceedings of the IEEE International Conference on Image Processing, 2013