Stephen Becker
Computational Mechanics · 2009–2014
A researcher in the Science corpus: 4 papers; trusts 72 researchers and is trusted by 88 researchers here, as inferred from the citation graph.
Subfields
- Computational Mechanics — 88 citations into it; #374 of 10,001 by trust here, #464 by citations
- Computer Vision and Pattern Recognition — 38 citations into it; #4,837 of 21,575 by trust here, #8,502 by citations
- Optimization & Training — 36 citations into it
- Mathematical Physics — 23 citations into it; #962 of 8,562 by trust here, #1,838 by citations
- Mathematical Optimization — 22 citations into it
- Artificial Intelligence — 20 citations into it; #12,122 of 35,345 by trust here, #8,525 by citations
- Numerical Analysis — 19 citations into it
- Biomedical Engineering — 18 citations into it; #537 of 10,734 by trust here, #5,210 by citations
Whom Stephen Becker trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yurii E. Nesterov
- E.J. Candes
- Patrick L. Combettes
- Antonin Chambolle
- Robert Tibshirani
- David L. Donoho
- Mário A. T. Figueiredo
- R. Tyrrell Rockafellar
- Ewout van den Berg
- Stephen J. Wright
Who trusts Stephen Becker overall
- E.J. Candes
- Chengbo Li
- Alexandre Belloni
- Guanghui Lan
- Paul Tseng
- Jasper Snoek
- Stephen P. Boyd
- Lin Xiao
- Neal Parikh
- Xiaoqun Zhang
Papers from Stephen Becker's perspective
Ordered by how strongly the researchers Stephen Becker trusts endorse each paper. Same corpus, a different order for every researcher.
- Regression Shrinkage and Selection via the Lasso
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Atomic Decomposition by Basis Pursuit
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
Their papers
- NESTA: A Fast and Accurate First-Order Method for Sparse Recovery (2009) — 1,227 citations
- Quantum state tomography via compressed sensing. (2009) — 1,120 citations
- Templates for convex cone problems with applications to sparse signal recovery (2010) — 693 citations
- Convex Optimization for Big Data: Scalable, randomized, and parallel algorithms for big data analytics (2014) — 308 citations