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2020 – today
- 2024
[j39]Minda Zhao, Zehua Lai, Lek-Heng Lim:
Stochastic Steffensen method. Comput. Optim. Appl. 89(1): 1-32 (2024)- [j38]Zhen Dai, Lek-Heng Lim, Ke Ye:
Complex matrix inversion via real matrix inversions. Numerische Mathematik 156(6): 2179-2219 (2024) - [i40]Rongbiao Wang, JungHo Lee, Lek-Heng Lim:
Summing divergent matrix series. CoRR abs/2405.19713 (2024) - [i39]Zehua Lai, Lek-Heng Lim, Ke Ye:
Simple matrix expressions for the curvatures of Grassmannian. CoRR abs/2406.11821 (2024) - [i38]Zehua Lai, Lek-Heng Lim, Ke Ye:
Grassmannian optimization is NP-hard. CoRR abs/2406.19377 (2024) - [i37]Lek-Heng Lim, Ke Ye:
Simple matrix models for the flag, Grassmann, and Stiefel manifolds. CoRR abs/2407.13482 (2024) - [i36]Zehua Lai, Lek-Heng Lim, Yucong Liu:
Attention is a smoothed cubic spline. CoRR abs/2408.09624 (2024) - 2023
- [j37]Zhen Dai, Lek-Heng Lim:
Numerical stability and tensor nuclear norm. Numerische Mathematik 155(3-4): 345-376 (2023) - [j36]Zihao Li, Lek-Heng Lim:
Generalized Matrix Nearness Problems. SIAM J. Matrix Anal. Appl. 44(4): 1709-1730 (2023) - [i35]Yian Chen, Yuehaw Khoo, Lek-Heng Lim:
Convex Relaxation for Fokker-Planck. CoRR abs/2306.03292 (2023) - 2022
- [j35]Brian St. Thomas, Kisung You
, Lizhen Lin, Lek-Heng Lim, Sayan Mukherjee:
Learning Subspaces of Different Dimensions. J. Comput. Graph. Stat. 31(1): 337-350 (2022) - [j34]Shmuel Friedland, Jean-Bernard Lasserre, Lek-Heng Lim, Jiawang Nie:
Special Issue: Polynomial and Tensor Optimization. Math. Program. 193(2): 511-512 (2022) - [j33]Ke Ye, Ken Sze-Wai Wong, Lek-Heng Lim:
Optimization on flag manifolds. Math. Program. 194(1): 621-660 (2022) - [j32]Yuhang Cai, Lek-Heng Lim:
Distances Between Probability Distributions of Different Dimensions. IEEE Trans. Inf. Theory 68(6): 4020-4031 (2022) - [i34]Lek-Heng Lim, Bradley J. Nelson:
What is an equivariant neural network? CoRR abs/2205.07362 (2022) - [i33]Zhen Dai, Lek-Heng Lim:
Numerical stability and tensor nuclear norm. CoRR abs/2207.08769 (2022) - [i32]Zhen Dai, Lek-Heng Lim:
Rank-constrained Hyperbolic Programming. CoRR abs/2207.11299 (2022) - [i31]Zhen Dai, Lek-Heng Lim, Ke Ye:
Inverting a complex matrix. CoRR abs/2208.01239 (2022) - [i30]Zihao Li, Lek-Heng Lim:
Generalized matrix nearness problems. CoRR abs/2209.14954 (2022) - [i29]Yucong Liu, Simiao Jiao, Lek-Heng Lim:
LU decomposition and Toeplitz decomposition of a neural network. CoRR abs/2211.13935 (2022) - [i28]Minda Zhao, Zehua Lai, Lek-Heng Lim:
Stochastic Steffensen method. CoRR abs/2211.15310 (2022) - 2021
- [j31]Lek-Heng Lim:
Tensors in computations. Acta Numer. 30: 555-764 (2021) - [j30]Lek-Heng Lim, Ken Sze-Wai Wong, Ke Ye:
The Grassmannian of affine subspaces. Found. Comput. Math. 21(2): 537-574 (2021) - [j29]Jose Israel Rodriguez, Jin-Hong Du, Yiling You, Lek-Heng Lim:
Fiber product homotopy method for multiparameter eigenvalue problems. Numerische Mathematik 148(4): 853-888 (2021) - [i27]Lek-Heng Lim:
Tensors in computations. CoRR abs/2106.08090 (2021) - 2020
- [j28]Gregory Naitzat, Andrey Zhitnikov, Lek-Heng Lim:
Topology of Deep Neural Networks. J. Mach. Learn. Res. 21: 184:1-184:40 (2020) - [j27]Lek-Heng Lim:
Hodge Laplacians on Graphs. SIAM Rev. 62(3): 685-715 (2020) - [c9]Zehua Lai, Lek-Heng Lim:
Recht-Re Noncommutative Arithmetic-Geometric Mean Conjecture is False. ICML 2020: 5608-5617 - [c8]Lek-Heng Lim, Ke Ye:
Ubiquity of the exponent of matrix multiplication. ISSAC 2020: 8-11 - [i26]Shmuel Friedland, Lek-Heng Lim:
Symmetric Grothendieck inequality. CoRR abs/2003.07345 (2020) - [i25]Gregory Naitzat, Andrey Zhitnikov, Lek-Heng Lim:
Topology of deep neural networks. CoRR abs/2004.06093 (2020) - [i24]Zehua Lai, Lek-Heng Lim:
Recht-Ré Noncommutative Arithmetic-Geometric Mean Conjecture is False. CoRR abs/2006.01510 (2020) - [i23]Yuhang Cai, Lek-Heng Lim:
Distances between probability distributions of different dimensions. CoRR abs/2011.00629 (2020)
2010 – 2019
- 2019
- [j26]Shmuel Friedland, Lek-Heng Lim, Jinjie Zhang:
Grothendieck constant is norm of Strassen matrix multiplication tensor. Numerische Mathematik 143(4): 905-922 (2019) - [j25]Lek-Heng Lim, Ken Sze-Wai Wong, Ke Ye:
Numerical Algorithms on the Affine Grassmannian. SIAM J. Matrix Anal. Appl. 40(2): 371-393 (2019) - [j24]Lek-Heng Lim, Rodolphe Sepulchre, Ke Ye:
Geometric Distance Between Positive Definite Matrices of Different Dimensions. IEEE Trans. Inf. Theory 65(9): 5401-5405 (2019) - [c7]Yang Qi, Pierre Comon, Lek-Heng Lim, Ke Ye:
Path-connectedness of tensor ranks. EUSIPCO 2019: 1-5 - [i22]Lek-Heng Lim, Mateusz Michalek, Yang Qi:
Best k-layer neural network approximations. CoRR abs/1907.01507 (2019) - 2018
- [j23]Ke Ye, Lek-Heng Lim:
Fast Structured Matrix Computations: Tensor Rank and Cohn-Umans Method. Found. Comput. Math. 18(1): 45-95 (2018) - [j22]Shmuel Friedland, Lek-Heng Lim:
Nuclear norm of higher-order tensors. Math. Comput. 87(311): 1255-1281 (2018) - [c6]Liwen Zhang, Gregory Naitzat, Lek-Heng Lim:
Tropical Geometry of Deep Neural Networks. ICML 2018: 5819-5827 - [i21]Liwen Zhang, Gregory Naitzat, Lek-Heng Lim:
Tropical Geometry of Deep Neural Networks. CoRR abs/1805.07091 (2018) - [i20]Tingran Gao, Lek-Heng Lim, Ke Ye:
Semi-Riemannian Manifold Optimization. CoRR abs/1812.07643 (2018) - 2017
- [j21]Michael Ankele, Lek-Heng Lim, Samuel Groeschel, Thomas Schultz:
Versatile, robust, and efficient tractography with constrained higher-order tensor fODFs. Int. J. Comput. Assist. Radiol. Surg. 12(8): 1257-1270 (2017) - [j20]Lek-Heng Lim:
Self-concordance is NP-hard. J. Glob. Optim. 68(2): 357-366 (2017) - [j19]Ke Ye, Lek-Heng Lim:
Cohomology of Cryo-Electron Microscopy. SIAM J. Appl. Algebra Geom. 1(1): 507-535 (2017) - [j18]Austin R. Benson, David F. Gleich, Lek-Heng Lim:
The Spacey Random Walk: A Stochastic Process for Higher-Order Data. SIAM Rev. 59(2): 321-345 (2017) - [j17]Lek-Heng Lim, Jonathan Weare:
Fast Randomized Iteration: Diffusion Monte Carlo through the Lens of Numerical Linear Algebra. SIAM Rev. 59(3): 547-587 (2017) - [i19]Jinjie Zhang, Lek-Heng Lim:
Grothendieck constant is norm of Strassen matrix multiplication tensor. CoRR abs/1711.04427 (2017) - 2016
- [j16]Ke Ye, Lek-Heng Lim:
Every Matrix is a Product of Toeplitz Matrices. Found. Comput. Math. 16(3): 577-598 (2016) - [j15]Shmuel Friedland, Lek-Heng Lim:
The Computational Complexity of Duality. SIAM J. Optim. 26(4): 2378-2393 (2016) - [j14]Ke Ye, Lek-Heng Lim:
Schubert Varieties and Distances between Subspaces of Different Dimensions. SIAM J. Matrix Anal. Appl. 37(3): 1176-1197 (2016) - [j13]Yang Qi, Pierre Comon, Lek-Heng Lim:
Semialgebraic Geometry of Nonnegative Tensor Rank. SIAM J. Matrix Anal. Appl. 37(4): 1556-1580 (2016) - [j12]Yang Qi, Pierre Comon, Lek-Heng Lim:
Uniqueness of Nonnegative Tensor Approximations. IEEE Trans. Inf. Theory 62(4): 2170-2183 (2016) - [c5]Ke Ye, Lek-Heng Lim:
Algorithms for structured matrix-vector product of optimal bilinear complexity. ITW 2016: 310-314 - [c4]Michael Ankele, Lek-Heng Lim, Samuel Groeschel, Thomas Schultz:
Fast and Accurate Multi-tissue Deconvolution Using SHORE and H-psd Tensors. MICCAI (3) 2016: 502-510 - [i18]Shmuel Friedland, Lek-Heng Lim:
The Computational Complexity of Duality. CoRR abs/1601.07629 (2016) - [i17]Austin R. Benson, David F. Gleich, Lek-Heng Lim:
The Spacey Random Walk: a Stochastic Process for Higher-order Data. CoRR abs/1602.02102 (2016) - [i16]Ke Ye, Lek-Heng Lim:
Cohomology of Cryo-Electron Microscopy. CoRR abs/1604.01319 (2016) - 2015
- [j11]David F. Gleich, Lek-Heng Lim, Yongyang Yu:
Multilinear PageRank. SIAM J. Matrix Anal. Appl. 36(4): 1507-1541 (2015) - [c3]Arun Rajkumar, Suprovat Ghoshal, Lek-Heng Lim, Shivani Agarwal:
Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top. ICML 2015: 665-673 - [i15]Lek-Heng Lim:
Hodge Laplacians on graphs. CoRR abs/1507.05379 (2015) - 2014
- [j10]Lek-Heng Lim, Pierre Comon:
Blind Multilinear Identification. IEEE Trans. Inf. Theory 60(2): 1260-1280 (2014) - [p1]Thomas Schultz, Andrea Fuster, Aurobrata Ghosh, Rachid Deriche, Luc Florack, Lek-Heng Lim:
Higher-Order Tensors in Diffusion Imaging. Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data 2014: 129-161 - [i14]David F. Gleich, Lek-Heng Lim, Yongyang Yu:
Multilinear PageRank. CoRR abs/1409.1465 (2014) - [i13]Shmuel Friedland, Lek-Heng Lim:
Computational Complexity of Tensor Nuclear Norm. CoRR abs/1410.6072 (2014) - [i12]Yang Qi, Pierre Comon, Lek-Heng Lim:
Uniqueness of Nonnegative Tensor Approximations. CoRR abs/1410.8129 (2014) - 2013
- [j9]Christopher J. Hillar, Lek-Heng Lim:
Most Tensor Problems Are NP-Hard. J. ACM 60(6): 45:1-45:39 (2013) - [j8]Ming Gu, Lek-Heng Lim, Cinna Julie Wu:
ParNes: a rapidly convergent algorithm for accurate recovery of sparse and approximately sparse signals. Numer. Algorithms 64(2): 321-347 (2013) - [j7]Lek-Heng Lim, Michael K. Ng, Liqun Qi:
The spectral theory of tensors and its applications. Numer. Linear Algebra Appl. 20(6): 889-890 (2013) - [i11]Lek-Heng Lim:
Self-concordance is NP-hard. CoRR abs/1303.7455 (2013) - 2012
- [i10]Lek-Heng Lim, Pierre Comon:
Blind Multilinear Identification. CoRR abs/1212.6663 (2012) - 2011
- [j6]Xiaoye Jiang, Lek-Heng Lim, Yuan Yao, Yinyu Ye:
Statistical ranking and combinatorial Hodge theory. Math. Program. 127(1): 203-244 (2011) - [c2]David F. Gleich, Lek-Heng Lim:
Rank aggregation via nuclear norm minimization. KDD 2011: 60-68 - [i9]David F. Gleich, Lek-Heng Lim:
Rank Aggregation via Nuclear Norm Minimization. CoRR abs/1102.4821 (2011) - 2010
- [j5]Berkant Savas, Lek-Heng Lim:
Quasi-Newton Methods on Grassmannians and Multilinear Approximations of Tensors. SIAM J. Sci. Comput. 32(6): 3352-3393 (2010) - [i8]Lek-Heng Lim, Pierre Comon:
Multiarray Signal Processing: Tensor decomposition meets compressed sensing. CoRR abs/1002.4935 (2010)
2000 – 2009
- 2009
- [i7]Lek-Heng Lim, Pierre Comon:
Nonnegative approximations of nonnegative tensors. CoRR abs/0903.4530 (2009) - [i6]Ming Gu, Lek-Heng Lim, Cinna Julie Wu:
PARNES: A rapidly convergent algorithm for accurate recovery of sparse and approximately sparse signals. CoRR abs/0911.0492 (2009) - [i5]Christopher J. Hillar, Lek-Heng Lim:
Most tensor problems are NP hard. CoRR abs/0911.1393 (2009) - 2008
- [j4]Morten Mørup, Lars Kai Hansen, Sidse Marie Arnfred, Lek-Heng Lim, Kristoffer Hougaard Madsen:
Shift-invariant multilinear decomposition of neuroimaging data. NeuroImage 42(4): 1439-1450 (2008) - [j3]Vin de Silva, Lek-Heng Lim:
Tensor Rank and the Ill-Posedness of the Best Low-Rank Approximation Problem. SIAM J. Matrix Anal. Appl. 30(3): 1084-1127 (2008) - [j2]Pierre Comon, Gene H. Golub, Lek-Heng Lim, Bernard Mourrain:
Symmetric Tensors and Symmetric Tensor Rank. SIAM J. Matrix Anal. Appl. 30(3): 1254-1279 (2008) - [j1]Michael W. Mahoney, Lek-Heng Lim, Gunnar E. Carlsson:
Algorithmic and statistical challenges in modern largescale data analysis are the focus of MMDS 2008. SIGKDD Explor. 10(2): 57-60 (2008) - [i4]Xiaoye Jiang, Lek-Heng Lim, Yuan Yao, Yinyu Ye:
Learning to rank with combinatorial Hodge theory. CoRR abs/0811.1067 (2008) - [i3]Michael W. Mahoney, Lek-Heng Lim, Gunnar E. Carlsson:
Algorithmic and Statistical Challenges in Modern Large-Scale Data Analysis are the Focus of MMDS 2008. CoRR abs/0812.3702 (2008) - 2006
- [c1]Pierre Comon, Bernard Mourrain, Lek-Heng Lim, Gene H. Golub:
Genericity And Rank Deficiency Of High Order Symmetric Tensors. ICASSP (3) 2006: 125-128 - [i2]Lek-Heng Lim:
Singular Values and Eigenvalues of Tensors: A Variational Approach. CoRR abs/math/0607648 (2006) - 2000
- [i1]Lek-Heng Lim:
Security of the Cao-Li Public Key Cryptosystem. CoRR cs.CR/0003053 (2000)
Coauthor Index
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