Garvesh Raskutti

Statistics and Probability · 2008–2012

A researcher in the Science corpus: 7 papers; trusts 62 researchers and is trusted by 80 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 80 citations into it; #662 of 12,932 by trust here, #475 by citations
• Artificial Intelligence — 40 citations into it; #19,753 of 35,345 by trust here, #23,077 by citations
• Computational Mechanics — 40 citations into it; #757 of 10,001 by trust here, #642 by citations
• Statistical Learning Theory — 35 citations into it
• Signal Processing — 13 citations into it
• Computer Networks and Communications — 12 citations into it; #3,734 of 9,886 by trust here, #2,300 by citations
• Applied Mathematics — 10 citations into it
• Optimization & Training — 10 citations into it

Whom Garvesh Raskutti trusts overall

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

1. Michel Ledoux
2. Bin Yu
3. Martin J. Wainwright
4. Nicolai Meinshausen
5. S. Jammalamadaka
6. Robert Tibshirani
7. Sara A. van de Geer
8. Cun-Hui Zhang
9. Peter Buhlmann
10. E.J. Candes

Who trusts Garvesh Raskutti overall

1. Martin J. Wainwright
2. Alekh Agarwal
3. Sahand N. Negahban
4. Sara A. van de Geer
5. Dougal Maclaurin
6. Yuchen Zhang
7. Nicolai Meinshausen
8. Taiji Suzuki
9. Peter Buhlmann
10. Kengo Kato

Papers from Garvesh Raskutti's perspective

Ordered by how strongly the researchers Garvesh Raskutti 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. Regression Shrinkage and Selection via the Lasso
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence (2008) — 914 citations
• Restricted Eigenvalue Properties for Correlated Gaussian Designs (2010) — 530 citations
• Minimax Rates of Estimation for High-Dimensional Linear Regression Over q -Balls (2009) — 596 citations
• Geometry of the faithfulness assumption in causal inference (2012) — 260 citations
• Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming (2010) — 302 citations
• Early stopping for non-parametric regression: An optimal data-dependent stopping rule (2011) — 336 citations
• Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness (2009) — 27 citations