Kairan Yang

Optimization & Training · 2019

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 5 citations into it

Whom Kairan Yang trusts overall

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

1. Jorge Nocedal
2. H. Brendan McMahan
3. Richard H. Byrd
4. Yoshinori Aono
5. Jakub Konecný
6. Stephen Hardy
7. Stephen J. Wright
8. Pascal Paillier
9. N. Schraudolph
10. Philipp Moritz

Who trusts Kairan Yang overall

1. Xuefei Yin
2. Yanming Zhu

Papers from Kairan Yang's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Numerical optimization
7. A Stochastic Quasi-Newton Method for Online Convex Optimization
8. Learning Multiple Layers of Features from Tiny Images
9. A Stochastic Quasi-Newton Method for Large-Scale Optimization
10. Communication-Efficient Learning of Deep Networks from Decentralized Data

Their papers

• A Quasi-Newton Method Based Vertical Federated Learning Framework for Logistic Regression (2019) — 101 citations