Fetching the paper…
Reading the bibliography…
Tensor models play an increasingly prominent role in many fields, notably in machine learning.
The expression of a tensor or a polyadic as a sum of products
F. L. Hitchcock · 1927
Earlier work this paper cites.
Some mathematical notes on three-mode factor analysis
L. R. Tucker · 1966
Earlier work this paper cites.
Estimation of the mean of a multivariate normal distribution
C. M. Stein · 1981
Earlier work this paper cites.
Review of chemometrics applied to spectroscopy: 1985-95, part 3—multi-way analysis
R. Bro, J. J. Workman JR., P. R. Mobley, and B. R. Kowalski · 1997
Earlier work this paper cites.
Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices
J. Baik, G. Ben Arous, and S. Péché · 2005
Earlier work this paper cites.
Singular values and eigenvalues of tensors: a variational approach
L.-H. Lim · 2005
Earlier work this paper cites.
Numerical optimization
J. Nocedal and S. Wright · 2006
Earlier work this paper cites.
Spectral analysis of large dimensional random matrices
Z. Bai and J. W. Silverstein · 2010
Earlier work this paper cites.
The eigenvalues and eigenvectors of finite, low rank perturbations of large random matrices
F. Benaych-Georges and R. R. Nadakuditi · 2011
Earlier work this paper cites.
Shifted power method for computing tensor eigenpairs
T. G. Kolda and J. R. Mayo · 2011
Earlier work this paper cites.
Applications of tensor (multiway array) factorizations and decompositions in data mining
M. Mørup · 2011
Earlier work this paper cites.
Eigenvalue distribution of large random matrices
L. A. Pastur and M. Shcherbina · 2011
Earlier work this paper cites.
Tensor Spaces and Numerical Tensor Calculus
W. Hackbusch · 2012
Earlier work this paper cites.
Tensors: Geometry and Applications , volume 128 of Graduate Studies in Mathematics
J. M. Landsberg · 2012
Earlier work this paper cites.
Graph spectra and the detectability of community structure in networks
R. R. Nadakuditi and M. E. J. Newman · 2012
Earlier work this paper cites.
Topics in random matrix theory , volume 132
T. Tao · 2012
Earlier work this paper cites.
Most tensor problems are NP-hard
C. J. Hillar and L.-H. Lim · 2013
Cited alongside, same era.
The implicit function theorem: history, theory, and applications
S. G. Krantz and H. R. Parks · 2013
Cited alongside, same era.
Tensor decompositions for learning latent variable models
A. Anandkumar, D. Hsu, S. M. Kakade, and M. Telgarsky · 2014
Cited alongside, same era.
Provable tensor factorization with missing data
P. Jain and S. Oh · 2014
Cited alongside, same era.
A statistical model for tensor PCA
A. Montanari and E. Richard · 2014
Cited alongside, same era.
Escaping from saddle points — online stochastic gradient for tensor decomposition
R. Ge, F. Huang, C. Jin, and Y. Yuan · 2015
Cited alongside, same era.
The dynamics of learning: A random matrix approach
Z. Liao and R. Couillet · 2018
Later among the works it cites.
A random matrix analysis and improvement of semi-supervised learning for large dimensional data
X. Mai and R. Couillet · 2018
Later among the works it cites.
The landscape of the spiked tensor model
G. Ben Arous, S. Mei, A. Montanari, and M. Nica · 2019
Later among the works it cites.
Phase transition in the spiked random tensor with Rademacher prior
W.-K. Chen · 2019
Later among the works it cites.
A large dimensional analysis of least squares support vector machines
Z. Liao and R. Couillet · 2019
Later among the works it cites.
A large scale analysis of logistic regression: Asymptotic performance and new insights
X. Mai, Z. Liao, and R. Couillet · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Tensor principal component analysis via sum-of-square proofs
S. B. Hopkins, J. Shi, and D. Steurer · 2015
Cited alongside, same era.
Provable models for robust low-rank tensor completion
B. Huang, C. Mu, D. Goldfarb, and J. Wright · 2015
Cited alongside, same era.
Kernel spectral clustering of large dimensional data
R. Couillet and F. Benaych-Georges · 2016
Cited alongside, same era.
Statistical and computational phase transitions in spiked tensor estimation
T. Lesieur, L. Miolane, M. Lelarge, F. Krzakala, and L. Zdeborova · 2017
Cited alongside, same era.
On the limitation of spectral methods: From the Gaussian hidden clique problem to rank one perturbations of Gaussian tensors
A. Montanari, D. Reichman, and O. Zeitouni · 2017
Cited alongside, same era.
Tensor analysis: spectral theory and special tensors
L. Qi and Z. Luo · 2017
Cited alongside, same era.
High-dimensional dynamics of generalization error in neural networks
M. S. Advani, A. M. Saxe, and H. Sompolinsky · 2020
Later among the works it cites.
Statistical thresholds for Tensor PCA
A. Jagannath, P. Lopatto, and L. Miolane · 2020
Later among the works it cites.
Statistical limits of spiked tensor models
A. Perry, A. S. Wein, and A. S. Bandeira · 2020
Later among the works it cites.
Deciphering and optimizing multi-task learning: a random matrix approach
M. Tiomoko, H. T. Ali, and R. Couillet · 2020
Later among the works it cites.
Spectral asymptotics for contracted tensor ensembles
B. Au and J. Garza-Vargas · 2021
Closest in time.
Long random matrices and tensor unfolding
G. Ben Arous, D. Z. Huang, and J. Huang · 2021
Closest in time.
Phase transition in random tensors with multiple independent spikes
W.-K. Chen, M. Handschy, and G. Lerman · 2021
Closest in time.
On the precise error analysis of support vector machines
A. Kammoun and M.-S. Alouini · 2021
Closest in time.
Consistent semi-supervised graph regularization for high dimensional data
X. Mai and R. Couillet · 2021
Closest in time.