Michael Zibulevsky

Computational Mechanics · 2001–2010

A researcher in the Science corpus: 6 papers; trusts 39 researchers and is trusted by 44 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 44 citations into it; #1,339 of 10,001 by trust here, #2,112 by citations
• Computer Vision and Pattern Recognition — 37 citations into it; #8,141 of 21,575 by trust here, #12,689 by citations
• Signal Processing — 25 citations into it; #700 of 7,572 by trust here, #1,299 by citations
• Optimization & Training — 13 citations into it
• Biomedical Engineering — 11 citations into it; #4,219 of 10,734 by trust here, #8,044 by citations
• Media Technology — 10 citations into it
• Representation & Self-Supervised Learning — 10 citations into it; #2,037 of 3,145 by trust here, #2,624 by citations
• Statistical Learning Theory — 8 citations into it

Whom Michael Zibulevsky trusts overall

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

1. David L. Donoho
2. Stéphane Mallat
3. Michael Elad
4. Robert Tibshirani
5. Scott Shaobing Chen
6. Joel A. Tropp
7. Aapo Hyvärinen
8. Michal Aharon
9. Julien Mairal
10. E.J. Candes

Who trusts Michael Zibulevsky overall

1. Aapo Hyvärinen
2. Sarit Shwartz
3. Lionel Mathelin
4. Ruohan Gao
5. Weisheng Dong
6. Emmanuel Vincent
7. Yuanqing Li
8. Xiaofeng Ren
9. Hossein Mohimani
10. Einav Namer

Papers from Michael Zibulevsky's perspective

Ordered by how strongly the researchers Michael Zibulevsky 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. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. GENERATIVE ADVERSARIAL NETS
9. Long Short-Term Memory
10. Regression Shrinkage and Selection via the Lasso

Their papers

• L1-L2 Optimization in Signal and Image Processing (2010) — 463 citations
• Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation (2010) — 644 citations
• On the Uniqueness of Nonnegative Sparse Solutions to Underdetermined Systems of Equations (2008) — 311 citations
• Efficient Implementation of the K-SVD Algorithm using Batch Orthogonal Matching Pursuit (2008) — 844 citations
• Blind Source Separation by Sparse Decomposition in a Signal Dictionary (2001) — 859 citations
• Underdetermined blind source separation using sparse representations (2001) — 792 citations