Zemin Zhang
Computational Mechanics · with Aeron · 2014–2015
A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Computational Mechanics — 18 citations into it; #2,523 of 10,001 by trust here, #4,749 by citations
- Computational Mathematics — 17 citations into it; #177 of 612 by trust here, #279 by citations
- Computational Theory and Mathematics — 10 citations into it
- Artificial Intelligence — 9 citations into it
- Computer Vision and Pattern Recognition — 6 citations into it; #18,600 of 21,575 by trust here, #15,955 by citations
- Representation & Self-Supervised Learning — 5 citations into it
- Signal Processing — 5 citations into it; #2,513 of 7,572 by trust here, #6,355 by citations
Whom Zemin Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- B. Recht
- E.J. Candes
- Carla D. Moravitz Martin
- Lars Grasedyck
- Misha Elena Kilmer
- David Gross
- Karen S. Braman
- Jian-Feng Cai
- Tamara G. Kolda
- Silvia Gandy
Who trusts Zemin Zhang overall
- Canyi Lu
- Yun Miao
- Pan Zhou
- Jiashi Feng
- Liqun Qi
- Landan Zhang
- Zhouchen Lin
- Seunghyun Lee
- Eric Kernfeld
- Shuchin Aeron
Papers from Zemin Zhang's perspective
Ordered by how strongly the researchers Zemin Zhang trusts endorse each paper. Same corpus, a different order for every researcher.
- Exact Matrix Completion via Convex Optimization
- ImageNet classification with deep convolutional neural networks
- Tensor Decompositions and Applications
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- A Singular Value Thresholding Algorithm for Matrix Completion
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Novel Methods for Multilinear Data Completion and De-noising Based on Tensor-SVD (2014) — 793 citations
- Exact Tensor Completion Using t-SVD (2015) — 660 citations