Ayush Sekhari

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Computational Mechanics — 13 citations into it
• Optimization & Training — 10 citations into it
• Privacy & Security — 10 citations into it
• Statistical Learning Theory — 6 citations into it

Whom Ayush Sekhari trusts overall

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

1. Cynthia Dwork
2. Shai Shalev-Shwartz
3. Gert Cauwenberghs
4. Seth Neel
5. Zeyuan Allen-Zhu
6. Raef Bassily
7. Chuan Guo
8. Antonio A. Ginart
9. Zachary Izzo
10. Frank McSherry

Who trusts Ayush Sekhari overall

1. Ruiqi Zhang
2. Anvith Thudi
3. Varun Gupta
4. Jingwen Ye
5. Licong Lin
6. Gabriel Deza

Papers from Ayush Sekhari's perspective

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

Their papers

• Remember What You Want to Forget: Algorithms for Machine Unlearning (2021) — 475 citations
• The Complexity of Making the Gradient Small in Stochastic Convex Optimization (2019) — 60 citations