Saeed Ghadimi

Optimization & Training · 2012–2018

A researcher in the Science corpus: 6 papers; trusts 37 researchers and is trusted by 294 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 62 citations into it; #154 of 2,601 by trust here, #363 by citations
• Artificial Intelligence — 43 citations into it; #909 of 35,345 by trust here, #2,660 by citations
• Computational Mechanics — 36 citations into it; #62 of 10,001 by trust here, #191 by citations
• Numerical Analysis — 27 citations into it; #221 of 3,586 by trust here, #405 by citations
• Management Science and Operations Research — 26 citations into it; #72 of 11,946 by trust here, #206 by citations
• Mathematical Optimization — 25 citations into it; #50 of 422 by trust here, #89 by citations
• Statistics and Probability — 23 citations into it
• Computational Theory and Mathematics — 15 citations into it; #8,492 of 12,182 by trust here, #10,901 by citations

Whom Saeed Ghadimi trusts overall

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

1. Yurii E. Nesterov
2. Guanghui Lan
3. Alexander Shapiro
4. Anatoli B. Juditsky
5. Tim Hesterberg
6. Boris Polyak
7. Arkadi Nemirovski
8. Coralia Cartis
9. Chonghai Hu
10. Lin Xiao

Who trusts Saeed Ghadimi overall

1. Guanghui Lan
2. Zeyuan Allen-Zhu
3. Sashank J. Reddi
4. Suvrit Sra
5. Damek Davis
6. Tianbao Yang
7. Simon Lacoste-Julien
8. John C. Duchi
9. Xiangru Lian
10. Yi Xu

Papers from Saeed Ghadimi's perspective

Ordered by how strongly the researchers Saeed Ghadimi 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Regression Shrinkage and Selection via the Lasso
6. Learning Multiple Layers of Features from Tiny Images
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Attention is All you Need (Neural Information Processing Systems)
10. A Stochastic Approximation Method

Their papers

• Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming (2013) — 1,919 citations
• Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization I: A Generic Algorithmic Framework (2012) — 398 citations
• Accelerated gradient methods for nonconvex nonlinear and stochastic programming (2013) — 627 citations
• Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization, II: Shrinking Procedures and Optimal Algorithms (2013) — 230 citations
• Mini-batch stochastic approximation methods for nonconvex stochastic composite optimization (2013) — 565 citations
• Approximation Methods for Bilevel Programming (2018) — 388 citations