Eric King-Wah Chu

Computational Mechanics · 2001–2013

A researcher in the Science corpus: 10 papers; trusts 30 researchers and is trusted by 32 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 59 citations into it; #5,190 of 10,001 by trust here, #4,178 by citations
• Computer Vision and Pattern Recognition — 29 citations into it
• Numerical Analysis — 29 citations into it; #529 of 3,586 by trust here, #371 by citations
• Optimization & Training — 27 citations into it; #1,199 of 2,601 by trust here, #232 by citations
• Computational Theory and Mathematics — 22 citations into it; #2,829 of 12,182 by trust here, #2,161 by citations
• Control and Systems Engineering — 19 citations into it; #3,790 of 8,257 by trust here, #6,417 by citations
• Mathematical Physics — 19 citations into it
• Numerical Methods & Scientific Computing — 17 citations into it

Whom Eric King-Wah Chu trusts overall

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

1. Patrick L. Combettes
2. Stephen P. Boyd
3. Stephen J. Wright
4. E.J. Candes
5. R. Tyrrell Rockafellar
6. Tom Goldstein
7. Y. Saad
8. Timothy A. Davis
9. Ingrid Daubechies
10. Antonin Chambolle

Who trusts Eric King-Wah Chu overall

1. Brendan O'Donoghue
2. Thomas Morstyn
3. M. G. Tehrani
4. Stephen P. Boyd
5. Brett Robbins
6. Gitta Kutyniok
7. Ali H. Sayed
8. J. Mottershead
9. Steven Diamond
10. Mohammad Rostami

Papers from Eric King-Wah Chu's perspective

Ordered by how strongly the researchers Eric King-Wah Chu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Regression Shrinkage and Selection via the Lasso
2. ImageNet classification with deep convolutional neural networks
3. An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Atomic Decomposition by Basis Pursuit
9. Gradient-based learning applied to document recognition
10. ImageNet: A large-scale hierarchical image database

Their papers

• Conic Optimization via Operator Splitting and Homogeneous Self-Dual Embedding (2013) — 844 citations
• Using Near-Field Stereo Vision for Robotic Grasping in Cluttered Environments (2010) — 28 citations
• ECOS: An SOCP solver for embedded systems (2013) — 834 citations
• Dynamic Network Energy Management via Proximal Message Passing (2013) — 335 citations
• Structure-Preserving Algorithms for Periodic Discrete-Time Algebraic Riccati Equations (2004) — 100 citations
• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers (2011) — 8,037 citations
• Vibration of fast trains, palindromic eigenvalue problems and structure-preserving doubling algorithms (2008) — 56 citations
• A structure-preserving doubling algorithm for continuous-time algebraic Riccati equations (2005) — 119 citations
• POLE ASSIGNMENT FOR SECOND-ORDER SYSTEMS (2002) — 81 citations
• Optimization and pole assignment in control system design (2001) — 46 citations