Perceptual hashing of color images using hypercomplex representations. - Issam H. Laradji; Lahouari Ghouti; El-Hebri Khiari (ICIP, 2013)

XML classification using ensemble learning on extracted features. - Issam H. Laradji; Salahadin Mohammed; Lahouari Ghouti (ACM Southeast Regional Conference, 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 (ICANN, 2014)

Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection. - Julie Nutini; Mark Schmidt 001; Issam H. Laradji; Michael P. Friedlander; Hoyt A. Koepke (ICML, 2015)

Software defect prediction using ensemble learning on selected features. - Issam H. Laradji; Mohammad R. Alshayeb; Lahouari Ghouti (Inf. Softw. Technol., 2015)

Convergence Rates for Greedy Kaczmarz Algorithms, and Randomized Kaczmarz Rules Using the Orthogonality Graph. - Julie Nutini; Behrooz Sepehry; Issam H. Laradji; Mark Schmidt 001; Hoyt A. Koepke; Alim Virani (UAI, 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 001; Hoyt A. Koepke; Alim Virani (CoRR, 2016)

Where Are the Blobs: Counting by Localization with Point Supervision. - Issam H. Laradji; Negar Rostamzadeh; Pedro O. Pinheiro; David Vázquez 001; Mark Schmidt 001 (ECCV (2), 2018)

MASAGA: A Linearly-Convergent Stochastic First-Order Method for Optimization on Manifolds. - Reza Babanezhad 001; Issam H. Laradji; Alireza Shafaei; Mark Schmidt 001 (ECML/PKDD (2), 2018)

M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning. - Issam H. Laradji; Reza Babanezhad 001 (CoRR, 2018)

Where are the Masks: Instance Segmentation with Image-level Supervision. - Issam H. Laradji; David Vázquez 001; Mark Schmidt 001 (BMVC, 2019)

Class-Based Styling: Real-Time Localized Style Transfer with Semantic Segmentation. - Lironne Kurzman; David Vázquez 001; Issam H. Laradji (ICCV Workshops, 2019)

Efficient Deep Gaussian Process Models for Variable-Sized Inputs. - Issam H. Laradji; Mark Schmidt 001; Vladimir Pavlovic 001; Minyoung Kim 001 (IJCNN, 2019)

Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. - Sharan Vaswani; Aaron Mishkin; Issam H. Laradji; Mark Schmidt 001; Gauthier Gidel; Simon Lacoste-Julien (NeurIPS, 2019)

Efficient Deep Gaussian Process Models for Variable-Sized Input. - Issam H. Laradji; Mark Schmidt 001; Vladimir Pavlovic 001; Minyoung Kim 001 (CoRR, 2019)

Instance Segmentation with Point Supervision. - Issam H. Laradji; Negar Rostamzadeh; Pedro O. Pinheiro; David Vázquez 001; Mark Schmidt 001 (CoRR, 2019)

M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning. - Issam H. Laradji; Reza Babanezhad 001 (Domain Adaptation for Visual Understanding, 2020)

Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation. - Si Yi Meng; Sharan Vaswani; Issam Hadj Laradji; Mark Schmidt 001; Simon Lacoste-Julien (AISTATS, 2020)

Embedding Propagation: Smoother Manifold for Few-Shot Classification. - Pau Rodríguez; Issam H. Laradji; Alexandre Drouin; Alexandre Lacoste (ECCV (26), 2020)

Looc: Localize Overlapping Objects with Count Supervision. - Issam H. Laradji; Rafael Pardinas; Pau Rodríguez; David Vázquez 001 (ICIP, 2020)

Proposal-Based Instance Segmentation With Point Supervision. - Issam H. Laradji; Negar Rostamzadeh; Pedro O. Pinheiro; David Vázquez 001; Mark Schmidt 001 (ICIP, 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 001; Laurent Charlin (NeurIPS, 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 001 (NeurIPS, 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 001; Laurent Charlin (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 001; Simon Lacoste-Julien (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)

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 001; Derek Nowrouzezahrai (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 001; Marcus Sheaves (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 001 (CoRR, 2020)

Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery. - Issam H. Laradji; Pau Rodríguez; Freddie Kalaitzis; David Vázquez 001; Ross Young; Ed Davey; Alexandre Lacoste (CoRR, 2020)

Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. - Nicolas Loizou; Sharan Vaswani; Issam Hadj Laradji; Simon Lacoste-Julien (AISTATS, 2021)

Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. - Pau Rodríguez; Massimo Caccia; Alexandre Lacoste; Lee Zamparo; Issam H. Laradji; Laurent Charlin; David Vázquez 001 (ICCV, 2021)

SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction. - Issam H. Laradji; Pau Rodríguez; David Vázquez 001; Derek Nowrouzezahrai (ICCVW, 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 001; Derek Nowrouzezahrai (WACV, 2021)

Learning Data Augmentation with Online Bilevel Optimization for Image Classification. - Saypraseuth Mounsaveng; Issam H. Laradji; Ismail Ben Ayed; David Vázquez 001; Marco Pedersoli (WACV, 2021)

A Deep Learning Localization Method for Measuring Abdominal Muscle Dimensions in Ultrasound Images. - Alzayat Saleh; Issam H. Laradji; Corey Lammie; David Vázquez 001; Carol A. Flavell; Mostafa Rahimi Azghadi (IEEE J. Biomed. Health Informatics, 2021)

Data Augmentation for Intent Classification with Off-the-shelf Large Language Models. - Gaurav Sahu; Pau Rodríguez; Issam H. Laradji; Parmida Atighehchian; David Vázquez 001; Dzmitry Bahdanau (ConvAI@ACL, 2022)

Consistency-CAM: Towards Improved Weakly Supervised Semantic Segmentation. - Sai Rajeswar; Issam Hadj Laradji; Pau Rodríguez; David Vázquez 001; Aaron C. Courville (BMVC, 2022)

OSM: An Open Set Matting Framework with OOD Detection and Few-Shot Learning. - Yuhongze Zhou; Issam Hadj Laradji; Liguang Zhou; Derek Nowrouzezahrai (BMVC, 2022)

Overcoming challenges in leveraging GANs for few-shot data augmentation. - Christopher Beckham; Issam H. Laradji; Pau Rodríguez; David Vázquez 001; Derek Nowrouzezahrai; Christopher Pal (CoLLAs, 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; et al. (CVPR, 2022)

Neural Point Light Fields. - Julian Ost; Issam H. Laradji; Alejandro Newell; Yuval Bahat; Felix Heide (CVPR, 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 001; Zheda Mai; David Vázquez 001; German Ignacio Parisi; Nikhil Churamani; et al. (Artif. Intell., 2022)

Challenges in leveraging GANs for few-shot data augmentation. - Christopher Beckham; Issam H. Laradji; Pau Rodríguez; David Vázquez 001; Derek Nowrouzezahrai; Christopher J. Pal (CoRR, 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 001 (J. Mach. Learn. Res., 2022)

TK-KNN: A Balanced Distance-Based Pseudo Labeling Approach for Semi-Supervised Intent Classification. - Nicholas Botzer; David Vasquez; Tim Weninger; Issam H. Laradji (EMNLP (Findings), 2023)

LLM aided semi-supervision for efficient Extractive Dialog Summarization. - Nishant Mishra; Gaurav Sahu; Iacer Calixto; Ameen Abu-Hanna; Issam H. Laradji (EMNLP (Findings), 2023)

PromptMix: A Class Boundary Augmentation Method for Large Language Model Distillation. - Gaurav Sahu; Olga Vechtomova; Dzmitry Bahdanau; Issam H. Laradji (EMNLP, 2023)

Affinity Learning With Blind-Spot Self-Supervision for Image Denoising. - Yuhongze Zhou; Liguang Zhou; Issam Hadj Laradji; Tin Lun Lam; Yangsheng Xu (ICASSP, 2023)

Constraining Representations Yields Models That Know What They Don't Know. - João Monteiro 002; Pau Rodríguez; Pierre-André Noël; Issam H. Laradji; David Vázquez 001 (ICLR, 2023)

FigGen: Text to Scientific Figure Generation. - Juan A. Rodríguez; David Vázquez 001; Issam H. Laradji; Marco Pedersoli; Pau Rodríguez (Tiny Papers @ ICLR, 2023)

OCR-VQGAN: Taming Text-within-Image Generation. - Juan A. Rodríguez; David Vázquez 001; Issam H. Laradji; Marco Pedersoli; Pau Rodríguez (WACV, 2023)

Long-Context Language Decision Transformers and Exponential Tilt for Interactive Text Environments. - Nicolas Gontier; Pau Rodríguez; Issam H. Laradji; David Vázquez 001; Christopher Pal (CoRR, 2023)

Automatic Data Augmentation Learning using Bilevel Optimization for Histopathological Images. - Saypraseuth Mounsaveng; Issam H. Laradji; David Vázquez 001; Marco Pedersoli; Ismail Ben Ayed (CoRR, 2023)

Enchancing Semi-Supervised Learning for Extractive Summarization with an LLM-based pseudolabeler. - Gaurav Sahu; Olga Vechtomova; Issam H. Laradji (CoRR, 2023)

LLM aided semi-supervision for Extractive Dialog Summarization. - Nishant Mishra; Gaurav Sahu; Iacer Calixto; Ameen Abu-Hanna; Issam H. Laradji (CoRR, 2023)

StarVector: Generating Scalable Vector Graphics Code from Images. - Juan A. Rodríguez; Shubham Agarwal; Issam H. Laradji; Pau Rodríguez; David Vázquez 001; Christopher Pal; Marco Pedersoli (CoRR, 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 001; Christopher Pal; Alexandre Drouin (CoRR, 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)

Workflow Discovery from Dialogues in the Low Data Regime. - Amine El Hattami; Issam H. Laradji; Stefania Raimondo; David Vázquez 001; Pau Rodríguez; Christopher Pal (Trans. Mach. Learn. Res., 2023)

Explaining Visual Counterfactual Explainers. - Diego A. Velázquez; Pau Rodríguez; Alexandre Lacoste; Issam H. Laradji; F. Xavier Roca; Jordi Gonzàlez 001 (Trans. Mach. Learn. Res., 2023)

A Survey of Self-Supervised and Few-Shot Object Detection. - Gabriel Huang; Issam H. Laradji; David Vázquez 001; Simon Lacoste-Julien; Pau Rodríguez (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

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 001; Nicolas Chapados; Alexandre Lacoste (ICML, 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; Léo Boisvert; Megh Thakkar; Quentin Cappart; David Vázquez 001; Nicolas Chapados; Alexandre Lacoste (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 001 (CoRR, 2024)

InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation. - Gaurav Sahu; Abhay Puri; Juan A. Rodríguez; Alexandre Drouin; Perouz Taslakian; Valentina Zantedeschi; Alexandre Lacoste; David Vázquez 001; Nicolas Chapados; Christopher Pal; Sai Rajeswar; Issam Hadj Laradji (CoRR, 2024)

MixSumm: Topic-based Data Augmentation using LLMs for Low-resource Extractive Text Summarization. - Gaurav Sahu; Issam H. Laradji (CoRR, 2024)

IntentGPT: Few-shot Intent Discovery with Large Language Models. - Juan A. Rodríguez; Nicholas Botzer; David Vázquez 001; Christopher Pal; Marco Pedersoli; Issam H. Laradji (CoRR, 2024)

BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks. - Juan A. Rodríguez; Xiangru Jian; Siba Smarak Panigrahi; Tianyu Zhang; Aarash Feizi; Abhay Puri; Akshay Kalkunte; François Savard; Ahmed Masry; Shravan Nayak; Rabiul Awal; Mahsa Massoud; et al. (CoRR, 2024)

FM2DS: Few-Shot Multimodal Multihop Data Synthesis with Knowledge Distillation for Question Answering. - Amirhossein Abaskohi; Spandana Gella; Giuseppe Carenini; Issam H. Laradji (CoRR, 2024)

LLMs for Literature Review: Are we there yet? - Shubham Agarwal; Gaurav Sahu; Abhay Puri; Issam H. Laradji; Krishnamurthy Dj Dvijotham; Jason Stanley; Laurent Charlin; Christopher Pal (CoRR, 2024)

StarVector: Generating Scalable Vector Graphics Code from Images and Text. - Juan A. Rodríguez; Abhay Puri; Shubham Agarwal; Issam H. Laradji; Sai Rajeswar; David Vázquez 001; Christopher Pal; Marco Pedersoli (AAAI, 2025)

Fast Convergence of Softmax Policy Mirror Ascent. - Reza Asad; Reza Babanezhad Harikandeh; Issam H. Laradji; Nicolas Le Roux; Sharan Vaswani (AISTATS, 2025)

StarVector: Generating Scalable Vector Graphics Code from Images and Text. - Juan A. Rodríguez; Abhay Puri; Shubham Agarwal; Issam H. Laradji; Pau Rodríguez; Sai Rajeswar; David Vázquez 001; Christopher Pal; Marco Pedersoli (CVPR, 2025)

InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation. - Gaurav Sahu; Abhay Puri; Juan A. Rodríguez; Amirhossein Abaskohi; Mohammad Chegini; Alexandre Drouin; Perouz Taslakian; Valentina Zantedeschi; Alexandre Lacoste; David Vázquez 001; Nicolas Chapados; Christopher Pal; et al. (ICLR, 2025)

A Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches. - Gaurav Sahu; Olga Vechtomova; Issam H. Laradji (NAACL (Findings), 2025)

LitLLMs, LLMs for Literature Review: Are we there yet? - Shubham Agarwal; Gaurav Sahu; Abhay Puri; Issam H. Laradji; Krishnamurthy Dj Dvijotham; Jason Stanley; Laurent Charlin; Christopher Pal (Trans. Mach. Learn. Res., 2025)

AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding. - Ahmed Masry; Juan A. Rodríguez; Tianyu Zhang; Suyuchen Wang; Chao Wang; Aarash Feizi; Akshay Kalkunte Suresh; Abhay Puri; Xiangru Jian; Pierre-André Noël; Sathwik Tejaswi Madhusudhan; Marco Pedersoli; et al. (CoRR, 2025)

AgentAda: Skill-Adaptive Data Analytics for Tailored Insight Discovery. - Amirhossein Abaskohi; Amrutha Varshini Ramesh; Shailesh Nanisetty; Chirag Goel; David Vázquez 001; Christopher Pal; Spandana Gella; Giuseppe Carenini; Issam H. Laradji (CoRR, 2025)