Massih-Reza Amini

Artificial Intelligence · 2002–2022

A researcher in the Science corpus: 7 papers; trusts 78 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 94 citations into it
• Optimization & Training — 51 citations into it
• Computational Mechanics — 34 citations into it
• Computer Vision and Pattern Recognition — 33 citations into it
• Representation & Self-Supervised Learning — 21 citations into it; #2,359 of 3,145 by trust here, #2,624 by citations
• Natural Language Processing — 19 citations into it
• Computer Networks and Communications — 13 citations into it
• Statistics and Probability — 10 citations into it; #8,953 of 12,932 by trust here, #7,508 by citations

Whom Massih-Reza Amini trusts overall

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

1. Thorsten Joachims
2. Alex Krizhevsky
3. Kamal Nigam
4. Yoshua Bengio
5. Geoffrey E. Hinton
6. Peter L. Bartlett
7. Diederik P. Kingma
8. Dong-Hyun Lee
9. Yann LeCun
10. Kaiming He

Who trusts Massih-Reza Amini overall

1. Lixin Duan
2. Amir Najafi
3. Avleen Singh Bijral
4. Xiang Wang
5. Yang Zou
6. Wen Li
7. Hongliang Yan
8. Xiao Huang
9. Dong Xu
10. Yu Huang

Papers from Massih-Reza Amini's perspective

Ordered by how strongly the researchers Massih-Reza Amini trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Self-Training: A Survey (2022) — 195 citations
• Semi Supervised Logistic Regression (2002) — 104 citations
• A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning (2018) — 40 citations
• Distributed Learning with Sparse Communications by Identification (2018) — 8 citations
• Asynchronous Distributed Learning with Sparse Communications and Identification (2018) — 19 citations
• Multitask Learning for Fine-Grained Twitter Sentiment Analysis (2017) — 94 citations
• Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization (2009) — 383 citations