Issam Hadj Laradji
Artificial Intelligence · 2015–2022
A researcher in the Science corpus: 13 papers; trusts 722 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 379 citations into it; #13,354 of 35,345 by trust here, #10,065 by citations
- Optimization & Training — 261 citations into it; #1,312 of 2,601 by trust here, #1,537 by citations
- Computer Vision and Pattern Recognition — 236 citations into it
- Computational Mechanics — 161 citations into it; #6,346 of 10,001 by trust here, #5,813 by citations
- Management Science and Operations Research — 61 citations into it
- Representation & Self-Supervised Learning — 61 citations into it
- Statistics and Probability — 47 citations into it
- Evaluation & Benchmarks — 46 citations into it
Whom Issam Hadj Laradji trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Kaiming He
- Geoffrey E. Hinton
- Yoshua Bengio
- Ross B. Girshick
- Alex Krizhevsky
- L. Eon Bottou
- Yann LeCun
- Yurii E. Nesterov
- Mark W. Schmidt
Who trusts Issam Hadj Laradji overall
- Nicolas Loizou
- Chakkrit Kla Tantithamthavorn
- Antonio Orvieto
- Shane McIntosh
- Sebastian U. Stich
- Simon Lacoste-Julien
- Julie Nutini
- Robert Mansel Gower
- Sharan Vaswani
- Mark W. Schmidt
Papers from Issam Hadj Laradji's perspective
Ordered by how strongly the researchers Issam Hadj Laradji trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Kubric: A scalable dataset generator (2022) — 467 citations
- Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning (2020) — 68 citations
- Where are the Blobs: Counting by Localization with Point Supervision (2018) — 218 citations
- Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection (2015) — 249 citations
- Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants via the Mirror Stochastic Polyak Stepsize (2021) — 42 citations
- CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions (2020) — 54 citations
- Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning (2020) — 80 citations
- Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence (2020) — 242 citations
- Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation (2019) — 40 citations
- Class-Based Styling: Real-Time Localized Style Transfer with Semantic Segmentation (2019) — 25 citations
- Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates (2019) — 247 citations
- Let's Make Block Coordinate Descent Go Fast: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence (2017) — 50 citations
- Software defect prediction using ensemble learning on selected features (2015) — 379 citations