Lek-Heng Lim
Computational Theory and Mathematics · 2005–2015
A researcher in the Science corpus: 9 papers; trusts 60 researchers and is trusted by 141 researchers here, as inferred from the citation graph.
Subfields
- Computational Theory and Mathematics — 49 citations into it; #84 of 12,182 by trust here, #182 by citations
- Computational Mathematics — 46 citations into it; #6 of 612 by trust here, #11 by citations
- Computational Mechanics — 38 citations into it; #684 of 10,001 by trust here, #1,006 by citations
- Signal Processing — 29 citations into it; #296 of 7,572 by trust here, #960 by citations
- Computer Vision and Pattern Recognition — 21 citations into it; #16,709 of 21,575 by trust here, #20,271 by citations
- Artificial Intelligence — 18 citations into it
- Statistics and Probability — 15 citations into it
- Numerical Methods & Scientific Computing — 14 citations into it
Whom Lek-Heng Lim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Lieven De Lathauwer
- Tomi Pannila
- B. De Moor
- Liqun Qi
- Joos Vandewalle
- László Babai
- Xiaoye Jiang
- Yurii E. Nesterov
- Douglas N. Arnold
- Gene H. Golub
Who trusts Lek-Heng Lim overall
- Liqun Qi
- Shmuel Friedland
- Boris N. Khoromskij
- Tamara G. Kolda
- Ivan V. Oseledets
- Kung-Ching Chang
- J. Shao
- Anima Anandkumar
- Chaoqian Li
- Joshua N. Cooper
Papers from Lek-Heng Lim's perspective
Ordered by how strongly the researchers Lek-Heng Lim trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Matrix Computations
- Gradient-based learning applied to document recognition
- A Multilinear Singular Value Decomposition
- Signal Processing based on Multilinear Algebra
- Tensor Decompositions and Applications
- Γ and B
- ImageNet: A large-scale hierarchical image database
- Regression Shrinkage and Selection via the Lasso
Their papers
- Tensor Rank and the Ill-Posedness of the Best Low-Rank Approximation Problem (2006) — 963 citations
- Singular values and eigenvalues of tensors: a variational approach (2005) — 1,090 citations
- Symmetric Tensors and Symmetric Tensor Rank (2008) — 652 citations
- Most Tensor Problems Are NP-Hard (2009) — 1,392 citations
- ParNes: a rapidly convergent algorithm for accurate recovery of sparse and approximately sparse signals (2009) — 30 citations
- Statistical ranking and combinatorial Hodge theory (2008) — 424 citations
- Quasi-Newton Methods on Grassmannians and Multilinear Approximations of Tensors (2009) — 137 citations
- Tensors and Hypermatrices (2013) — 126 citations
- Hodge Laplacians on graphs (2015) — 312 citations