Daichi Kitahara

Computational Mechanics · 2020

A researcher in the Science corpus: 1 paper; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 39 citations into it
• Computational Theory and Mathematics — 20 citations into it
• Mathematical Physics — 19 citations into it
• Optimization & Training — 15 citations into it
• Numerical Analysis — 14 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it
• Artificial Intelligence — 7 citations into it
• Mathematical Optimization — 5 citations into it

Whom Daichi Kitahara trusts overall

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

1. Patrick L. Combettes
2. Ming Yan
3. Laurent Condat
4. Tom Goldstein
5. Stanley J. Osher
6. Luis M. Briceño-Arias
7. Antonin Chambolle
8. Heinz H. Bauschke
9. Wotao Yin
10. Pierre-Louis Lions

Who trusts Daichi Kitahara overall

1. Adil Salim

Papers from Daichi Kitahara's perspective

Ordered by how strongly the researchers Daichi Kitahara 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. Splitting Algorithms for the Sum of Two Nonlinear Operators
5. Signal Recovery by Proximal Forward-Backward Splitting
6. Regression Shrinkage and Selection via the Lasso
7. The Split Bregman Method for L1-Regularized Problems
8. Gradient-based learning applied to document recognition
9. A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Proximal Splitting Algorithms: A Tour of Recent Advances, with New Twists. (2020) — 28 citations