Sushant Sachdeva
Artificial Intelligence · 2017–2022
A researcher in the Science corpus: 3 papers; trusts 17 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 58 citations into it; #34,301 of 35,345 by trust here, #19,873 by citations
- Optimization & Training — 55 citations into it
- Scaling & Learning Theory — 14 citations into it
- Computational Mechanics — 12 citations into it
- Computational Theory and Mathematics — 9 citations into it
Whom Sushant Sachdeva trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yuchen Zhang
- Ju Sun
- Rong Ge
- Diederik P. Kingma
- Shai Shalev-Shwartz
- Geoffrey E. Hinton
- Jason D. Lee
- Yoshua Bengio
- James Martens
- Yann LeCun
Who trusts Sushant Sachdeva overall
Papers from Sushant Sachdeva's perspective
Ordered by how strongly the researchers Sushant Sachdeva trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model (2019) — 192 citations
- Maximum Flow and Minimum-Cost Flow in Almost-Linear Time (2022) — 357 citations
- Convergence Results for Neural Networks via Electrodynamics (2017) — 22 citations