Baharan Mirzasoleiman

Artificial Intelligence · 2014–2021

A researcher in the Science corpus: 7 papers; trusts 74 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 71 citations into it; #13,295 of 35,345 by trust here, #14,718 by citations
• Optimization & Training — 46 citations into it; #2,318 of 2,601 by trust here, #2,081 by citations
• Computer Vision and Pattern Recognition — 29 citations into it
• Computational Theory and Mathematics — 16 citations into it; #3,988 of 12,182 by trust here, #4,059 by citations
• Natural Language Processing — 12 citations into it
• Computational Mechanics — 11 citations into it
• Model Architectures — 11 citations into it
• Management Science and Operations Research — 10 citations into it

Whom Baharan Mirzasoleiman trusts overall

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

1. Dimitri P. Bertsekas
2. Ashwinkumar Badanidiyuru
3. Andreas Krause
4. Tong Zhang
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Shai Shalev-Shwartz
8. George L. Nemhauser
9. Paul Tseng
10. John C. Duchi

Who trusts Baharan Mirzasoleiman overall

1. Krishnateja Killamsetty
2. Aditya Golatkar
3. Xujiang Zhao
4. Matthew Fahrbach
5. Amin Karbasi
6. Pierre Stock
7. Rishabh K. Iyer
8. Moran Feldman
9. Alessandro Achille
10. F. Chen

Papers from Baharan Mirzasoleiman's perspective

Ordered by how strongly the researchers Baharan Mirzasoleiman 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Selection Via Proxy: Efficient Data Selection For Deep Learning (2019) — 497 citations
• Streaming submodular maximization: massive data summarization on the fly (2014) — 387 citations
• Lazier Than Lazy Greedy (2014) — 472 citations
• GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training (2021) — 81 citations
• Coresets for Robust Training of Deep Neural Networks against Noisy Labels (2020) — 97 citations
• Coresets for Data-efficient Training of Machine Learning Models (2019) — 541 citations
• Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten" (2017) — 94 citations