Ian Waudby-Smith

Statistics and Probability · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 31 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 33 citations into it; #12,929 of 12,932 by trust here, #10,855 by citations
• Artificial Intelligence — 18 citations into it; #35,341 of 35,345 by trust here, #32,362 by citations
• Management Science and Operations Research — 14 citations into it
• Statistical Learning Theory — 6 citations into it
• Finance — 5 citations into it

Whom Ian Waudby-Smith trusts overall

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

1. Aaditya Ramdas
2. Steven R. Howard
3. Glenn Shafer
4. Akshay Balsubramani
5. Francesco Orabona
6. Nicolò Cesa-Bianchi
7. Jean-Yves Audibert
8. Alexandre B. Tsybakov
9. Victor H. de la Peña
10. Andreas Maurer

Who trusts Ian Waudby-Smith overall

1. Wei-Lin Chiang
2. Ruodu Wang
3. Lianmin Zheng
4. Edwin Fong

Papers from Ian Waudby-Smith's perspective

Ordered by how strongly the researchers Ian Waudby-Smith trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Gradient-based learning applied to document recognition
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Prediction, learning, and games
6. Regression Shrinkage and Selection via the Lasso
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. GENERATIVE ADVERSARIAL NETS
10. Long Short-Term Memory

Their papers

• Estimating means of bounded random variables by betting (2020) — 274 citations
• Time-uniform central limit theory and asymptotic confidence sequences (2021) — 52 citations