Amin Karbasi

Artificial Intelligence · 2011–2020

A researcher in the Science corpus: 8 papers; trusts 62 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 75 citations into it; #11,240 of 35,345 by trust here, #13,353 by citations
• Computational Theory and Mathematics — 39 citations into it; #4,126 of 12,182 by trust here, #3,796 by citations
• Optimization & Training — 32 citations into it; #2,428 of 2,601 by trust here, #2,081 by citations
• Computer Vision and Pattern Recognition — 29 citations into it
• Safety, Robustness & Interpretability — 25 citations into it; #1,961 of 2,251 by trust here, #1,907 by citations
• Algorithms & Complexity — 14 citations into it; #321 of 516 by trust here, #238 by citations
• Computer Graphics and Computer-Aided Design — 12 citations into it
• Natural Language Processing — 11 citations into it

Whom Amin Karbasi trusts overall

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

1. Ashwinkumar Badanidiyuru
2. Jon M. Kleinberg
3. Andreas Krause
4. George L. Nemhauser
5. Jure Leskovec
6. David R Karger
7. Robert Krauthgamer
8. Baharan Mirzasoleiman
9. Jan Vondr'ak
10. Christopher K. I. Williams

Who trusts Amin Karbasi overall

1. Aditya Golatkar
2. Baharan Mirzasoleiman
3. Pierre Stock
4. Matthew Fahrbach
5. Moran Feldman
6. Alessandro Achille
7. Christopher Harshaw
8. Ethan R. Elenberg
9. Yu A. Malkov
10. Moustapha Cissé

Papers from Amin Karbasi's perspective

Ordered by how strongly the researchers Amin Karbasi 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization (2020) — 73 citations
• Streaming submodular maximization: massive data summarization on the fly (2014) — 387 citations
• Lazier Than Lazy Greedy (2014) — 472 citations
• Submodular Maximization Beyond Non-negativity: Guarantees, Fast Algorithms, and Applications (2019) — 122 citations
• Submodular Maximization in Clean Linear Time (2020) — 27 citations
• Streaming Weak Submodularity: Interpreting Neural Networks on the Fly (2017) — 92 citations
• Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten" (2017) — 94 citations
• From Small-World Networks to Comparison-Based Search (2011) — 12 citations