Harikrishna Narasimhan

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 4 papers; trusts 34 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 52 citations into it
• Safety Research — 28 citations into it
• Optimization & Training — 27 citations into it
• Safety, Robustness & Interpretability — 20 citations into it
• AI Ethics, Fairness & Society — 15 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Harikrishna Narasimhan trusts overall

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

1. Martin Jaggi
2. Shuo Wang
3. Thorsten Joachims
4. Robert C. Williamson
5. Alekh Agarwal
6. George Forman
7. Andrew Cotter
8. Xin Yao
9. Tong Zhang
10. Moritz Hardt

Who trusts Harikrishna Narasimhan overall

1. Andrew Cotter
2. Heinrich Jiang
3. Yi Xu
4. Berk Ustun
5. Rachel Cummings
6. Ray Jiang
7. Tianbao Yang
8. Maya R. Gupta
9. Serena Wang
10. Yang Liu

Papers from Harikrishna Narasimhan's perspective

Ordered by how strongly the researchers Harikrishna Narasimhan 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
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

• Robust Optimization for Fairness with Noisy Protected Groups (2020) — 129 citations
• Pairwise Fairness for Ranking and Regression (2019) — 130 citations
• Learning with Complex Loss Functions and Constraints (2018) — 93 citations
• Consistent Multiclass Algorithms for Complex Performance Measures (2015) — 68 citations