Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1304.8087
Cited By
Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability
Annual Conference Computational Learning Theory (COLT), 2013
30 April 2013
Aditya Bhaskara
Moses Charikar
Aravindan Vijayaraghavan
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability"
30 / 30 papers shown
Low-Rank Tensor Recovery via Variational Schatten-p Quasi-Norm and Jacobian Regularization
Zhengyun Cheng
Ruizhe Zhang
Guanwen Zhang
Y. F. Xu
Xiangyang Ji
Wei Zhou
186
0
0
27 Jun 2025
Identifiability of Deep Polynomial Neural Networks
K. Usevich
Clara Dérand
Ricardo Augusto Borsoi
Marianne Clausel
195
3
0
20 Jun 2025
Joint Sensing, Communication, and AI: A Trifecta for Resilient THz User Experiences
IEEE Transactions on Wireless Communications (IEEE TWC), 2023
Christina Chaccour
Walid Saad
Merouane Debbah
H. Vincent Poor
257
32
0
29 Apr 2023
Reconstructing Training Data from Model Gradient, Provably
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Zihan Wang
Jason D. Lee
Qi Lei
FedML
301
34
0
07 Dec 2022
Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations
Neural Information Processing Systems (NeurIPS), 2021
Pranjal Awasthi
Alex K. Tang
Aravindan Vijayaraghavan
MLT
270
24
0
21 Jul 2021
Efficient Tensor Decomposition
Aravindan Vijayaraghavan
285
3
0
30 Jul 2020
Overcomplete order-3 tensor decomposition, blind deconvolution and Gaussian mixture models
SIAM Journal on Mathematics of Data Science (SIMODS), 2020
Haolin Chen
Luis Rademacher
318
3
0
16 Jul 2020
Learning an arbitrary mixture of two multinomial logits
Wenpin Tang
158
6
0
01 Jul 2020
Iterative Hard Thresholding for Low CP-rank Tensor Models
Linear and multilinear algebra (LMA), 2019
Rachel Grotheer
Shuang Li
A. Ma
Deanna Needell
Jing Qin
157
21
0
22 Aug 2019
Identifiability of Hierarchical Latent Attribute Models
Statistica sinica (Stat. Sinica), 2019
Yuqi Gu
Gongjun Xu
334
10
0
19 Jun 2019
Learning Attribute Patterns in High-Dimensional Structured Latent Attribute Models
Yuqi Gu
Gongjun Xu
228
26
0
08 Apr 2019
Overcomplete Independent Component Analysis via SDP
A. Podosinnikova
Amelia Perry
Alexander S. Wein
Francis R. Bach
Alexandre d’Aspremont
David Sontag
211
18
0
24 Jan 2019
Smoothed Analysis in Unsupervised Learning via Decoupling
Aditya Bhaskara
Aidao Chen
Aidan Perreault
Aravindan Vijayaraghavan
207
20
0
29 Nov 2018
Learning from Binary Multiway Data: Probabilistic Tensor Decomposition and its Statistical Optimality
Miaoyan Wang
Lexin Li
255
42
0
13 Nov 2018
Training Complex Models with Multi-Task Weak Supervision
Alexander Ratner
Braden Hancock
Jared A. Dunnmon
Frederic Sala
Shreyash Pandey
Christopher Ré
222
217
0
05 Oct 2018
Towards Learning Sparsely Used Dictionaries with Arbitrary Supports
IEEE Annual Symposium on Foundations of Computer Science (FOCS), 2018
Pranjal Awasthi
Aravindan Vijayaraghavan
289
7
0
23 Apr 2018
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling
Kejun Huang
Xiao Fu
N. Sidiropoulos
176
26
0
19 Feb 2018
Clustering Semi-Random Mixtures of Gaussians
Pranjal Awasthi
Aravindan Vijayaraghavan
150
13
0
23 Nov 2017
Better Agnostic Clustering Via Relaxed Tensor Norms
Pravesh Kothari
Jacob Steinhardt
222
61
0
20 Nov 2017
Learning Overcomplete HMMs
Willie Neiswanger
Sham Kakade
Abigail Z. Jacobs
Gregory Valiant
190
23
0
07 Nov 2017
On Learning Mixtures of Well-Separated Gaussians
O. Regev
Aravindan Vijayaraghavan
254
75
0
31 Oct 2017
Relative Error Tensor Low Rank Approximation
Zhao Song
David P. Woodruff
Peilin Zhong
226
125
0
26 Apr 2017
Tensor Decompositions via Two-Mode Higher-Order SVD (HOSVD)
Miaoyan Wang
Yun S. Song
159
6
0
12 Dec 2016
Agnostic Estimation of Mean and Covariance
Kevin A. Lai
Anup B. Rao
Santosh Vempala
251
359
0
24 Apr 2016
Dictionary Learning and Tensor Decomposition via the Sum-of-Squares Method
Symposium on the Theory of Computing (STOC), 2014
Boaz Barak
Jonathan A. Kelner
David Steurer
256
194
0
06 Jul 2014
Smoothed Analysis of Tensor Decompositions
Symposium on the Theory of Computing (STOC), 2013
Aditya Bhaskara
Moses Charikar
Ankur Moitra
Aravindan Vijayaraghavan
491
156
0
14 Nov 2013
The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures
Annual Conference Computational Learning Theory (COLT), 2013
Joseph Anderson
M. Belkin
Navin Goyal
Luis Rademacher
James R. Voss
368
96
0
12 Nov 2013
When are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity
Journal of machine learning research (JMLR), 2013
Anima Anandkumar
Daniel J. Hsu
Majid Janzamin
Sham Kakade
228
52
0
13 Aug 2013
Fourier PCA and Robust Tensor Decomposition
Symposium on the Theory of Computing (STOC), 2013
Navin Goyal
Santosh Vempala
Ying Xiao
431
98
0
25 Jun 2013
Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders
Sanjeev Arora
Rong Ge
Ankur Moitra
Sushant Sachdeva
365
87
0
23 Jun 2012
1
