Rashish Tandon

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 3 papers; trusts 11 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it; #16,987 of 35,345 by trust here, #21,316 by citations
• Computer Networks and Communications — 12 citations into it
• ML Systems & Hardware — 11 citations into it
• Hardware and Architecture — 5 citations into it

Whom Rashish Tandon trusts overall

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

1. Lisandro Dalcin
2. Kangwook Lee
3. Songze Li
4. Jianmin Chen
5. Rodrigo Paz
6. Qirong Ho
7. Maximilian Lam
8. Rajat Monga
9. Iroon Polytechniou
10. Mohammad Ali Maddah-Ali

Who trusts Rashish Tandon overall

1. Deepesh Data
2. Zachary B. Charles
3. Sanghamitra Dutta
4. Songze Li
5. Amirhossein Reisizadeh
6. Dimitris Papailiopoulos
7. Suhas N. Diggavi
8. Qian Yu
9. Can Bülent Karakus
10. Linqi Song

Papers from Rashish Tandon's perspective

Ordered by how strongly the researchers Rashish Tandon trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Gradient Coding: Avoiding Stragglers in Distributed Learning (2017) — 541 citations
• Gradient Coding From Cyclic MDS Codes and Expander Graphs (2017) — 199 citations
• Gradient Coding (2016) — 78 citations