Courtney Paquette

Optimization & Training · 2018

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 15 citations into it; #1,781 of 2,601 by trust here, #2,378 by citations
• Artificial Intelligence — 12 citations into it; #21,124 of 35,345 by trust here, #30,347 by citations

Whom Courtney Paquette trusts overall

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

1. Philipp Hennig
2. Diederik P. Kingma
3. Michael P. Friedlander
4. John C. Duchi
5. Maren Mahsereci
6. Abraham P. George
7. Bastian Goldlücke
8. Jorge Nocedal
9. Joel A. Tropp

Who trusts Courtney Paquette overall

1. El Houcine Bergou
2. Sharan Vaswani
3. Youssef Diouane
4. Aaron Mishkin
5. Issam Hadj Laradji

Papers from Courtney Paquette's perspective

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

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

Their papers

• A Stochastic Line Search Method with Convergence Rate Analysis (2018) — 53 citations
• Subgradient Methods for Sharp Weakly Convex Functions (2018) — 140 citations