Vivak Patel

Optimization & Training · 2015–2021

A researcher in the Science corpus: 3 papers; trusts 32 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 24 citations into it; #1,567 of 2,601 by trust here, #2,519 by citations
• Artificial Intelligence — 20 citations into it; #17,996 of 35,345 by trust here, #33,294 by citations
• Computational Mechanics — 14 citations into it; #4,847 of 10,001 by trust here, #9,276 by citations
• Statistics and Probability — 6 citations into it; #6,570 of 12,932 by trust here, #11,487 by citations

Whom Vivak Patel trusts overall

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

1. Dimitri P. Bertsekas
2. Ron Kohavi
3. L. Eon Bottou
4. Patrick L. Combettes
5. Shun-ichi Amari
6. Peter Richtárik
7. Ahmed Khaled
8. Olivier Bousquet
9. Shai Shalev-Shwartz
10. Tong Zhang

Who trusts Vivak Patel overall

1. S. Meng
2. Sharan Vaswani
3. Robert D. Kleinberg
4. Issam Hadj Laradji
5. Mark W. Schmidt
6. Simon Lacoste-Julien

Papers from Vivak Patel's perspective

Ordered by how strongly the researchers Vivak Patel 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. 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Stochastic Gradient Descent on Nonconvex Functions with General Noise Models (2021) — 10 citations
• Kalman-Based Stochastic Gradient Method with Stop Condition and Insensitivity to Conditioning (2015) — 35 citations
• The Impact of Local Geometry and Batch Size on the Convergence and Divergence of Stochastic Gradient Descent (2017) — 6 citations