Christiane Lemieux

Statistics and Probability · 2001–2009

A researcher in the Science corpus: 4 papers; trusts 66 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 32 citations into it; #1,382 of 12,932 by trust here, #4,650 by citations
• Numerical Analysis — 20 citations into it; #233 of 3,586 by trust here, #875 by citations
• Finance — 16 citations into it; #1,102 of 10,518 by trust here, #6,419 by citations
• Probabilistic & Bayesian Methods — 15 citations into it; #1,313 of 1,525 by trust here, #1,415 by citations
• Artificial Intelligence — 10 citations into it; #27,611 of 35,345 by trust here, #32,362 by citations
• Computer Vision and Pattern Recognition — 9 citations into it
• Management Science and Operations Research — 8 citations into it
• Computational Theory and Mathematics — 6 citations into it

Whom Christiane Lemieux trusts overall

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

1. Peter W. Glynn
2. Bradley Efron
3. Art B. Owen
4. Ilya M. Sobol
5. Paul Glasserman
6. Fred J. Hickernell
7. Reuven Y. Rubinstein
8. W. Hoeffding
9. Henryk Wozniakowski
10. Tim Hesterberg

Who trusts Christiane Lemieux overall

1. Zhonghua Han
2. Csaba Szepesvari
3. Josef Dick
4. Erich Novak
5. Tito Homem-de-Mello
6. Jean-Yves Tissot
7. Chris J. Oates
8. Stefan Görtz
9. Sushant S. Garud
10. Friedrich Pillichshammer

Papers from Christiane Lemieux's perspective

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

1. Random number generation and Quasi-Monte Carlo methods
2. ImageNet classification with deep convolutional neural networks
3. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Spline Models for Observational Data
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Learning Multiple Layers of Features from Tiny Images
8. Gradient-based learning applied to document recognition
9. Attention is All you Need (Neural Information Processing Systems)
10. Regression Shrinkage and Selection via the Lasso

Their papers

• Lattice Particle Filters (2001) — 26 citations
• Control variates for quasi-Monte Carlo (2005) — 80 citations
• Monte Carlo and Quasi-Monte Carlo Sampling (2009) — 615 citations
• Quasi-Regression and the Relative Importance of the ANOVA Components of a Function (2002) — 64 citations