Guillaume Lecué

Statistics and Probability · 2006–2017

A researcher in the Science corpus: 6 papers; trusts 76 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 126 citations into it; #4,759 of 12,932 by trust here, #4,964 by citations
• Artificial Intelligence — 66 citations into it
• Computational Mechanics — 37 citations into it; #4,907 of 10,001 by trust here, #7,501 by citations
• Statistical Learning Theory — 28 citations into it
• Management Science and Operations Research — 18 citations into it
• Control and Systems Engineering — 17 citations into it
• Applied Mathematics — 14 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it

Whom Guillaume Lecué trusts overall

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

1. Shahar Mendelson
2. Alexandre B. Tsybakov
3. Vladimir Koltchinskii
4. Sara A. van de Geer
5. E.J. Candes
6. Olivier Catoni
7. Lucien Birgé
8. Yuhong Yang
9. Robert Tibshirani
10. Gábor Lugosi

Who trusts Guillaume Lecué overall

1. Lesia Semenova
2. Cynthia Rudin
3. Gábor Lugosi
4. Tengyuan Liang
5. Aaron Fisher
6. Shahar Mendelson
7. Alexander Rakhlin
8. Zhiqiang Tan
9. Veronika Rocková
10. Karthik Sridharan

Papers from Guillaume Lecué's perspective

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

1. Regression Shrinkage and Selection via the Lasso
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. SIMULTANEOUS ANALYSIS OF LASSO AND DANTZIG SELECTOR
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. High-dimensional graphs and variable selection with the Lasso
8. Atomic Decomposition by Basis Pursuit
9. ImageNet: A large-scale hierarchical image database
10. Estimating the Dimension of a Model

Their papers

• Slope meets Lasso: Improved oracle bounds and optimality (2016) — 201 citations
• Robust machine learning by median-of-means: Theory and practice (2017) — 175 citations
• Aggregation via empirical risk minimization (2009) — 65 citations
• Interplay between concentration, complexity and geometry in learning theory with applications to high dimensional data analysis (2011) — 24 citations
• Optimal rates and adaptation in the single-index model using aggregation (2007) — 52 citations
• Adapting to Unknown Smoothness by Aggregation of Thresholded Wavelet Estimators (2006) — 10 citations