Mehdi Rezagholizadeh

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 5 papers; trusts 285 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 116 citations into it; #18,296 of 35,345 by trust here, #19,018 by citations
• Computer Vision and Pattern Recognition — 80 citations into it; #11,531 of 21,575 by trust here, #12,689 by citations
• Natural Language Processing — 60 citations into it
• Efficiency & Compression — 42 citations into it
• Model Architectures — 25 citations into it
• Large Language Models — 16 citations into it
• Generative Models — 13 citations into it
• Optimization & Training — 6 citations into it

Whom Mehdi Rezagholizadeh trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Ilya Sutskever
5. Yann LeCun
6. Diederik P. Kingma
7. Oriol Vinyals
8. Kaiming He
9. Sepp Hochreiter
10. Kyunghyun Cho

Who trusts Mehdi Rezagholizadeh overall

1. Sergey I. Nikolenko
2. Jianping Gou
3. Zeyu Han
4. Lingling Xu

Papers from Mehdi Rezagholizadeh's perspective

Ordered by how strongly the researchers Mehdi Rezagholizadeh trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• DyLoRA: Parameter-Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation (2022) — 309 citations
• Making a MIRACL: Multilingual Information Retrieval Across a Continuum of Languages (2022) — 71 citations
• ALP-KD: Attention-Based Layer Projection for Knowledge Distillation (2020) — 146 citations
• Fully Quantized Transformer for Machine Translation (2019) — 72 citations
• TextKD-GAN: Text Generation Using Knowledge Distillation and Generative Adversarial Networks (2019) — 54 citations