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ORCIDIssam H. Laradji
Issam Hadj Laradji
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2020 – today
- 2024
[c34]Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, David Vázquez, Nicolas Chapados, Alexandre Lacoste:
WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks? ICML 2024- [i48]Shubham Agarwal, Issam H. Laradji, Laurent Charlin, Christopher Pal:
LitLLM: A Toolkit for Scientific Literature Review. CoRR abs/2402.01788 (2024) - [i47]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:
WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks? CoRR abs/2403.07718 (2024) - [i46]Amrutha Varshini Ramesh, Vignesh Ganapathiraman, Issam H. Laradji, Mark Schmidt:
BlockLLM: Memory-Efficient Adaptation of LLMs by Selecting and Optimizing the Right Coordinate Blocks. CoRR abs/2406.17296 (2024) - [i45]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:
InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation. CoRR abs/2407.06423 (2024) - [i44]Gaurav Sahu, Issam H. Laradji:
MixSumm: Topic-based Data Augmentation using LLMs for Low-resource Extractive Text Summarization. CoRR abs/2407.07341 (2024) - 2023
- [j8]Gabriel Huang
, Issam H. Laradji, David Vázquez, Simon Lacoste-Julien, Pau Rodríguez:
A Survey of Self-Supervised and Few-Shot Object Detection. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4071-4089 (2023) - [j7]Ryan D'Orazio, Nicolas Loizou, Issam H. Laradji, Ioannis Mitliagkas:
Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants via the Mirror Stochastic Polyak Stepsize. Trans. Mach. Learn. Res. 2023 (2023) - [j6]Amine El Hattami, Issam H. Laradji, Stefania Raimondo, David Vázquez, Pau Rodríguez, Christopher Pal:
Workflow Discovery from Dialogues in the Low Data Regime. Trans. Mach. Learn. Res. 2023 (2023) - [j5]Diego A. Velázquez, Pau Rodríguez, Alexandre Lacoste, Issam H. Laradji, F. Xavier Roca, Jordi Gonzàlez:
Explaining Visual Counterfactual Explainers. Trans. Mach. Learn. Res. 2023 (2023) - [c33]Gaurav Sahu, Olga Vechtomova, Dzmitry Bahdanau, Issam H. Laradji:
PromptMix: A Class Boundary Augmentation Method for Large Language Model Distillation. EMNLP 2023: 5316-5327 - [c32]Nishant Mishra, Gaurav Sahu, Iacer Calixto, Ameen Abu-Hanna, Issam H. Laradji:
LLM aided semi-supervision for efficient Extractive Dialog Summarization. EMNLP (Findings) 2023: 10002-10009 - [c31]Yuhongze Zhou, Liguang Zhou, Issam Hadj Laradji, Tin Lun Lam, Yangsheng Xu:
Affinity Learning With Blind-Spot Self-Supervision for Image Denoising. ICASSP 2023: 1-5 - [c30]João Monteiro, Pau Rodríguez, Pierre-André Noël, Issam H. Laradji, David Vázquez:
Constraining Representations Yields Models That Know What They Don't Know. ICLR 2023 - [c29]Juan A. Rodriguez, David Vázquez, Issam H. Laradji, Marco Pedersoli, Pau Rodríguez:
FigGen: Text to Scientific Figure Generation. Tiny Papers @ ICLR 2023 - [c28]Juan A. Rodriguez, David Vázquez, Issam H. Laradji, Marco Pedersoli, Pau Rodríguez:
OCR-VQGAN: Taming Text-within-Image Generation. WACV 2023: 3678-3687 - [i43]Nicolas Gontier, Pau Rodríguez, Issam H. Laradji, David Vázquez, Christopher Pal:
Long-Context Language Decision Transformers and Exponential Tilt for Interactive Text Environments. CoRR abs/2302.05507 (2023) - [i42]Juan A. Rodriguez, David Vázquez, Issam H. Laradji, Marco Pedersoli, Pau Rodríguez:
FigGen: Text to Scientific Figure Generation. CoRR abs/2306.00800 (2023) - [i41]Saypraseuth Mounsaveng, Issam H. Laradji, David Vázquez, Marco Pedersoli, Ismail Ben Ayed:
Automatic Data Augmentation Learning using Bilevel Optimization for Histopathological Images. CoRR abs/2307.11808 (2023) - [i40]Gaurav Sahu, Olga Vechtomova, Dzmitry Bahdanau, Issam H. Laradji:
PromptMix: A Class Boundary Augmentation Method for Large Language Model Distillation. CoRR abs/2310.14192 (2023) - [i39]Gaurav Sahu, Olga Vechtomova, Issam H. Laradji:
Enchancing Semi-Supervised Learning for Extractive Summarization with an LLM-based pseudolabeler. CoRR abs/2311.09559 (2023) - [i38]Nishant Mishra, Gaurav Sahu, Iacer Calixto, Ameen Abu-Hanna, Issam H. Laradji:
LLM aided semi-supervision for Extractive Dialog Summarization. CoRR abs/2311.11462 (2023) - [i37]Juan A. Rodriguez, Shubham Agarwal, Issam H. Laradji, Pau Rodríguez, David Vázquez, Christopher Pal, Marco Pedersoli:
StarVector: Generating Scalable Vector Graphics Code from Images. CoRR abs/2312.11556 (2023) - [i36]Issam H. Laradji, Perouz Taslakian, Sai Rajeswar, Valentina Zantedeschi, Alexandre Lacoste, Nicolas Chapados, David Vázquez, Christopher Pal, Alexandre Drouin:
Capture the Flag: Uncovering Data Insights with Large Language Models. CoRR abs/2312.13876 (2023) - 2022
- [j4]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:
CVPR 2020 continual learning in computer vision competition: Approaches, results, current challenges and future directions. Artif. Intell. 303: 103635 (2022) - [j3]Julie Nutini, Issam H. Laradji, Mark Schmidt:
Let's Make Block Coordinate Descent Converge Faster: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence. J. Mach. Learn. Res. 23: 131:1-131:74 (2022) - [c27]Gaurav Sahu, Pau Rodríguez, Issam H. Laradji, Parmida Atighehchian, David Vázquez, Dzmitry Bahdanau:
Data Augmentation for Intent Classification with Off-the-shelf Large Language Models. ConvAI@ACL 2022: 47-57 - [c26]Yuhongze Zhou, Issam Hadj Laradji, Liguang Zhou, Derek Nowrouzezahrai:
OSM: An Open Set Matting Framework with OOD Detection and Few-Shot Learning. BMVC 2022: 92 - [c25]Sai Rajeswar, Issam Hadj Laradji, Pau Rodríguez, David Vázquez, Aaron C. Courville:
Consistency-CAM: Towards Improved Weakly Supervised Semantic Segmentation. BMVC 2022: 644 - [c24]Christopher Beckham, Issam H. Laradji, Pau Rodríguez, David Vázquez, Derek Nowrouzezahrai, Christopher Pal:
Overcoming challenges in leveraging GANs for few-shot data augmentation. CoLLAs 2022: 255-280 - [c23]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:
Kubric: A scalable dataset generator. CVPR 2022: 3739-3751 - [i35]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, 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:
Kubric: A scalable dataset generator. CoRR abs/2203.03570 (2022) - [i34]Christopher Beckham, Issam H. Laradji, Pau Rodríguez, David Vázquez, Derek Nowrouzezahrai, Christopher J. Pal:
Challenges in leveraging GANs for few-shot data augmentation. CoRR abs/2203.16662 (2022) - [i33]Gaurav Sahu, Pau Rodríguez, Issam H. Laradji, Parmida Atighehchian, David Vázquez, Dzmitry Bahdanau:
Data Augmentation for Intent Classification with Off-the-shelf Large Language Models. CoRR abs/2204.01959 (2022) - [i32]Amine El Hattami, Stefania Raimondo, Issam H. Laradji, David Vázquez, Pau Rodríguez, Chris Pal:
Workflow Discovery from Dialogues in the Low Data Regime. CoRR abs/2205.11690 (2022) - [i31]João Monteiro, Pau Rodríguez, Pierre-André Noël, Issam H. Laradji, David Vázquez:
Constraining Representations Yields Models That Know What They Don't Know. CoRR abs/2208.14488 (2022) - [i30]Juan A. Rodriguez, David Vázquez, Issam H. Laradji, Marco Pedersoli, Pau Rodríguez:
OCR-VQGAN: Taming Text-within-Image Generation. CoRR abs/2210.11248 (2022) - 2021
- [j2]Alzayat Saleh, Issam H. Laradji, Corey Lammie, David Vázquez, Carol A. Flavell, Mostafa Rahimi Azghadi:
A Deep Learning Localization Method for Measuring Abdominal Muscle Dimensions in Ultrasound Images. IEEE J. Biomed. Health Informatics 25(10): 3865-3873 (2021) - [c22]Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien:
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. AISTATS 2021: 1306-1314 - [c21]Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vázquez:
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. ICCV 2021: 1036-1045 - [c20]Issam H. Laradji, Pau Rodríguez, David Vázquez, Derek Nowrouzezahrai:
SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction. ICCVW 2021: 1427-1436 - [c19]Saypraseuth Mounsaveng, Issam H. Laradji, Ismail Ben Ayed, David Vázquez, Marco Pedersoli:
Learning Data Augmentation with Online Bilevel Optimization for Image Classification. WACV 2021: 1690-1699 - [c18]Issam H. Laradji, Pau Rodríguez, Oscar Mañas, Keegan Lensink, Marco Law, Lironne Kurzman, William Parker, David Vázquez, Derek Nowrouzezahrai:
A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images. WACV 2021: 2452-2461 - [i29]Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vázquez:
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. CoRR abs/2103.10226 (2021) - [i28]Issam H. Laradji, Pau Rodríguez, David Vázquez, Derek Nowrouzezahrai:
SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction. CoRR abs/2108.09593 (2021) - [i27]Alzayat Saleh, Issam H. Laradji, Corey Lammie, David Vázquez, Carol A. Flavell, Mostafa Rahimi Azghadi:
A Deep Learning Localization Method for Measuring Abdominal Muscle Dimensions in Ultrasound Images. CoRR abs/2109.14919 (2021) - [i26]Gabriel Huang, Issam H. Laradji, David Vázquez, Simon Lacoste-Julien, Pau Rodríguez:
A Survey of Self-Supervised and Few-Shot Object Detection. CoRR abs/2110.14711 (2021) - [i25]Ryan D'Orazio, Nicolas Loizou, Issam H. Laradji, Ioannis Mitliagkas:
Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants via the Mirror Stochastic Polyak Stepsize. CoRR abs/2110.15412 (2021) - 2020
- [c17]Si Yi Meng, Sharan Vaswani, Issam Hadj Laradji, Mark Schmidt, Simon Lacoste-Julien:
Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation. AISTATS 2020: 1375-1386 - [c16]Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste:
Embedding Propagation: Smoother Manifold for Few-Shot Classification. ECCV (26) 2020: 121-138 - [c15]Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro, David Vázquez, Mark Schmidt:
Proposal-Based Instance Segmentation With Point Supervision. ICIP 2020: 2126-2130 - [c14]Issam H. Laradji, Rafael Pardinas, Pau Rodríguez, David Vázquez:
Looc: Localize Overlapping Objects with Count Supervision. ICIP 2020: 2316-2320 - [c13]Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin:
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning. NeurIPS 2020 - [c12]Alexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez:
Synbols: Probing Learning Algorithms with Synthetic Datasets. NeurIPS 2020 - [p1]Issam H. Laradji, Reza Babanezhad:
M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning. Domain Adaptation for Visual Understanding 2020: 17-31 - [i24]Nicolas Loizou, Sharan Vaswani, Issam H. Laradji, Simon Lacoste-Julien:
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. CoRR abs/2002.10542 (2020) - [i23]Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste:
Embedding Propagation: Smoother Manifold for Few-Shot Classification. CoRR abs/2003.04151 (2020) - [i22]Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin:
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning. CoRR abs/2003.05856 (2020) - [i21]Sharan Vaswani, Frederik Kunstner, Issam H. Laradji, Si Yi Meng, Mark Schmidt, Simon Lacoste-Julien:
Adaptive Gradient Methods Converge Faster with Over-Parameterization (and you can do a line-search). CoRR abs/2006.06835 (2020) - [i20]Saypraseuth Mounsaveng, Issam H. Laradji, Ismail Ben Ayed, David Vázquez, Marco Pedersoli:
Learning Data Augmentation with Online Bilevel Optimization for Image Classification. CoRR abs/2006.14699 (2020) - [i19]Issam H. Laradji, Rafael Pardinas, Pau Rodríguez, David Vázquez:
LOOC: Localize Overlapping Objects with Count Supervision. CoRR abs/2007.01837 (2020) - [i18]Issam H. Laradji, Pau Rodríguez, Oscar Mañas, Keegan Lensink, Marco Law, Lironne Kurzman, William Parker, David Vázquez, Derek Nowrouzezahrai:
A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images. CoRR abs/2007.02180 (2020) - [i17]Keegan Lensink, Issam H. Laradji, Marco Law, Paolo Emilio Barbano, Savvas Nicolaou, William Parker, Eldad Haber:
Segmentation of Pulmonary Opacification in Chest CT Scans of COVID-19 Patients. CoRR abs/2007.03643 (2020) - [i16]Issam H. Laradji, Pau Rodríguez, Frederic Branchaud-Charron, Keegan Lensink, Parmida Atighehchian, William Parker, David Vázquez, Derek Nowrouzezahrai:
A Weakly Supervised Region-Based Active Learning Method for COVID-19 Segmentation in CT Images. CoRR abs/2007.07012 (2020) - [i15]Alzayat Saleh, Issam H. Laradji, Dmitry A. Konovalov, Michael Bradley, David Vázquez, Marcus Sheaves:
A Realistic Fish-Habitat Dataset to Evaluate Algorithms for Underwater Visual Analysis. CoRR abs/2008.12603 (2020) - [i14]Alexandre Lacoste, Pau Rodríguez, Frédéric Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam H. Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez:
Synbols: Probing Learning Algorithms with Synthetic Datasets. CoRR abs/2009.06415 (2020) - [i13]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:
CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions. CoRR abs/2009.09929 (2020) - [i12]Issam H. Laradji, Alzayat Saleh, Pau Rodríguez, Derek Nowrouzezahrai, Mostafa Rahimi Azghadi, David Vázquez:
Affinity LCFCN: Learning to Segment Fish with Weak Supervision. CoRR abs/2011.03149 (2020) - [i11]Issam H. Laradji, Pau Rodríguez, Freddie Kalaitzis, David Vázquez, Ross Young, Ed Davey, Alexandre Lacoste:
Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery. CoRR abs/2011.07369 (2020)
2010 – 2019
- 2019
- [c11]Issam H. Laradji, David Vázquez, Mark Schmidt:
Where are the Masks: Instance Segmentation with Image-level Supervision. BMVC 2019: 255 - [c10]Lironne Kurzman, David Vázquez, Issam H. Laradji:
Class-Based Styling: Real-Time Localized Style Transfer with Semantic Segmentation. ICCV Workshops 2019: 3189-3192 - [c9]Issam H. Laradji, Mark Schmidt, Vladimir Pavlovic, Minyoung Kim:
Efficient Deep Gaussian Process Models for Variable-Sized Inputs. IJCNN 2019: 1-7 - [c8]Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien:
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. NeurIPS 2019: 3727-3740 - [i10]Issam H. Laradji, Mark Schmidt, Vladimir Pavlovic, Minyoung Kim:
Efficient Deep Gaussian Process Models for Variable-Sized Input. CoRR abs/1905.06982 (2019) - [i9]Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien:
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. CoRR abs/1905.09997 (2019) - [i8]Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro, David Vázquez, Mark Schmidt:
Instance Segmentation with Point Supervision. CoRR abs/1906.06392 (2019) - [i7]Issam H. Laradji, David Vázquez, Mark Schmidt:
Where are the Masks: Instance Segmentation with Image-level Supervision. CoRR abs/1907.01430 (2019) - [i6]Lironne Kurzman, David Vázquez, Issam H. Laradji:
Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation. CoRR abs/1908.11525 (2019) - [i5]Si Yi Meng, Sharan Vaswani, Issam H. Laradji, Mark Schmidt, Simon Lacoste-Julien:
Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation. CoRR abs/1910.04920 (2019) - 2018
- [c7]Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro, David Vázquez, Mark Schmidt:
Where Are the Blobs: Counting by Localization with Point Supervision. ECCV (2) 2018: 560-576 - [c6]Reza Babanezhad, Issam H. Laradji, Alireza Shafaei, Mark Schmidt:
MASAGA: A Linearly-Convergent Stochastic First-Order Method for Optimization on Manifolds. ECML/PKDD (2) 2018: 344-359 - [i4]Issam H. Laradji, Reza Babanezhad:
M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning. CoRR abs/1807.02552 (2018) - [i3]Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro, David Vázquez, Mark Schmidt:
Where are the Blobs: Counting by Localization with Point Supervision. CoRR abs/1807.09856 (2018) - 2016
- [c5]Julie Nutini, Behrooz Sepehry, Issam H. Laradji, Mark Schmidt, Hoyt A. Koepke, Alim Virani:
Convergence Rates for Greedy Kaczmarz Algorithms, and Randomized Kaczmarz Rules Using the Orthogonality Graph. UAI 2016 - [i2]Julie Nutini, Behrooz Sepehry, Issam H. Laradji, Mark Schmidt, Hoyt A. Koepke, Alim Virani:
Convergence Rates for Greedy Kaczmarz Algorithms, and Faster Randomized Kaczmarz Rules Using the Orthogonality Graph. CoRR abs/1612.07838 (2016) - 2015
- [j1]Issam H. Laradji, Mohammad R. Alshayeb, Lahouari Ghouti:
Software defect prediction using ensemble learning on selected features. Inf. Softw. Technol. 58: 388-402 (2015) - [c4]Julie Nutini, Mark Schmidt, Issam H. Laradji, Michael P. Friedlander, Hoyt A. Koepke:
Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection. ICML 2015: 1632-1641 - [i1]Julie Nutini, Mark Schmidt, Issam H. Laradji, Michael P. Friedlander, Hoyt A. Koepke:
Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection. CoRR abs/1506.00552 (2015) - 2014
- [c3]Issam H. Laradji, Salahadin Mohammed, Lahouari Ghouti:
XML classification using ensemble learning on extracted features. ACM Southeast Regional Conference 2014: 1:1-1:6 - [c2]Issam H. Laradji, Lahouari Ghouti, Faisal Saleh, Musab A. AlTurki:
Sparse Single-Hidden Layer Feedforward Network for Mapping Natural Language Questions to SQL Queries. ICANN 2014: 241-248 - 2013
- [c1]Issam H. Laradji, Lahouari Ghouti, El-Hebri Khiari:
Perceptual hashing of color images using hypercomplex representations. ICIP 2013: 4402-4406
Coauthor Index
Pau Rodríguez
aka: Pau Rodríguez López
aka: Pau Rodríguez López
[c34] [i47] [i45] [j8] [j6] [c30] [c29] [c28] [i43] [i42] [i41] [i37] [i36] [j4] [c27] [c25] [c24] [i34] [i33] [i32] [i31] [i30] [j2] [c21] [c20] [c19] [c18] [i29] [i28] [i27] [i26] [c15] [c14] [c13] [c12] [i22] [i20] [i19] [i18] [i16] [i15] [i14] [i13] [i12] [i11] [c11] [c10] [i8] [i7] [i6] [c7] [i3]
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