ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1908.10935
  4. Cited By
Randomly initialized EM algorithm for two-component Gaussian mixture
  achieves near optimality in $O(\sqrt{n})$ iterations

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in O(n)O(\sqrt{n})O(n​) iterations

28 August 2019
Yihong Wu
Harrison H. Zhou
ArXiv (abs)PDFHTML

Papers citing "Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations"

33 / 33 papers shown
Title
Nonparametric MLE for Gaussian Location Mixtures: Certified Computation and Generic Behavior
Nonparametric MLE for Gaussian Location Mixtures: Certified Computation and Generic Behavior
Yury Polyanskiy
Mark Sellke
84
1
0
26 Mar 2025
How much is a noisy image worth? Data Scaling Laws for Ambient Diffusion
How much is a noisy image worth? Data Scaling Laws for Ambient Diffusion
Giannis Daras
Yeshwanth Cherapanamjeri
Constantinos Daskalakis
DiffM
101
9
0
05 Nov 2024
Semi-Supervised Sparse Gaussian Classification: Provable Benefits of
  Unlabeled Data
Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data
Eyar Azar
B. Nadler
67
1
0
05 Sep 2024
Factor Adjusted Spectral Clustering for Mixture Models
Factor Adjusted Spectral Clustering for Mixture Models
Shange Tang
Soham Jana
Jianqing Fan
112
1
0
22 Aug 2024
On the Convergence of a Federated Expectation-Maximization Algorithm
On the Convergence of a Federated Expectation-Maximization Algorithm
Zhixu Tao
Rajita Chandak
Sanjeev R. Kulkarni
FedML
93
0
0
11 Aug 2024
Toward Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixture Models
Toward Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixture Models
Weihang Xu
Maryam Fazel
S. Du
89
2
0
29 Jun 2024
Adaptive Mean Estimation in the Hidden Markov sub-Gaussian Mixture Model
Adaptive Mean Estimation in the Hidden Markov sub-Gaussian Mixture Model
V. Karagulyan
M. Ndaoud
77
0
0
18 Jun 2024
Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits
  and Optimal Spectral Methods
Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods
Yihan Zhang
Marco Mondelli
80
3
0
22 May 2024
Can semi-supervised learning use all the data effectively? A lower bound
  perspective
Can semi-supervised learning use all the data effectively? A lower bound perspective
Alexandru cTifrea
Gizem Yüce
Amartya Sanyal
Fanny Yang
111
3
0
30 Nov 2023
Joint Problems in Learning Multiple Dynamical Systems
Joint Problems in Learning Multiple Dynamical Systems
Mengjia Niu
Xiaoyu He
Petr Rysavý
Quan-Gen Zhou
Georgios Korpas
148
3
0
03 Nov 2023
Regularised optimal self-transport is approximate Gaussian mixture
  maximum likelihood
Regularised optimal self-transport is approximate Gaussian mixture maximum likelihood
Gilles Mordant
OT
84
2
0
23 Oct 2023
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing:
  The Curses of Symmetry and Initialization
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization
Nuoya Xiong
Lijun Ding
Simon S. Du
104
13
0
03 Oct 2023
EM for Mixture of Linear Regression with Clustered Data
EM for Mixture of Linear Regression with Clustered Data
Amirhossein Reisizadeh
Khashayar Gatmiry
Asuman Ozdaglar
FedML
45
1
0
22 Aug 2023
Demystifying Softmax Gating Function in Gaussian Mixture of Experts
Demystifying Softmax Gating Function in Gaussian Mixture of Experts
Huy Nguyen
TrungTin Nguyen
Nhat Ho
95
26
0
05 May 2023
Sharp-SSL: Selective high-dimensional axis-aligned random projections
  for semi-supervised learning
Sharp-SSL: Selective high-dimensional axis-aligned random projections for semi-supervised learning
Tengyao Wang
Yan Sun
M. Gataric
R. Samworth
61
1
0
18 Apr 2023
Sharp analysis of EM for learning mixtures of pairwise differences
Sharp analysis of EM for learning mixtures of pairwise differences
A. Dhawan
Cheng Mao
A. Pananjady
60
1
0
20 Feb 2023
Over-Parameterization Exponentially Slows Down Gradient Descent for
  Learning a Single Neuron
Over-Parameterization Exponentially Slows Down Gradient Descent for Learning a Single Neuron
Weihang Xu
S. Du
105
16
0
20 Feb 2023
Likelihood Adjusted Semidefinite Programs for Clustering Heterogeneous
  Data
Likelihood Adjusted Semidefinite Programs for Clustering Heterogeneous Data
Yubo Zhuang
Xiaohui Chen
Yun Yang
54
1
0
29 Sep 2022
Mean Estimation in High-Dimensional Binary Markov Gaussian Mixture
  Models
Mean Estimation in High-Dimensional Binary Markov Gaussian Mixture Models
Yihan Zhang
Nir Weinberger
36
0
0
06 Jun 2022
Optimal Estimation and Computational Limit of Low-rank Gaussian Mixtures
Optimal Estimation and Computational Limit of Low-rank Gaussian Mixtures
Zhongyuan Lyu
Dong Xia
64
9
0
22 Jan 2022
The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian
  Mixtures
The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures
Nir Weinberger
Guy Bresler
FedML
62
6
0
29 Mar 2021
Exact Clustering in Tensor Block Model: Statistical Optimality and
  Computational Limit
Exact Clustering in Tensor Block Model: Statistical Optimality and Computational Limit
Rungang Han
Yuetian Luo
Miaoyan Wang
Anru R. Zhang
122
39
0
18 Dec 2020
Local Minima Structures in Gaussian Mixture Models
Local Minima Structures in Gaussian Mixture Models
Yudong Chen
Dogyoon Song
Xumei Xi
Yuqian Zhang
38
3
0
28 Sep 2020
Likelihood Maximization and Moment Matching in Low SNR Gaussian Mixture
  Models
Likelihood Maximization and Moment Matching in Low SNR Gaussian Mixture Models
A. Katsevich
Afonso S. Bandeira
53
19
0
26 Jun 2020
On the Minimax Optimality of the EM Algorithm for Learning Two-Component
  Mixed Linear Regression
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression
Jeongyeol Kwon
Nhat Ho
Constantine Caramanis
54
39
0
04 Jun 2020
Uniform Convergence Rates for Maximum Likelihood Estimation under
  Two-Component Gaussian Mixture Models
Uniform Convergence Rates for Maximum Likelihood Estimation under Two-Component Gaussian Mixture Models
Tudor Manole
Nhat Ho
25
6
0
01 Jun 2020
Instability, Computational Efficiency and Statistical Accuracy
Instability, Computational Efficiency and Statistical Accuracy
Nhat Ho
K. Khamaru
Raaz Dwivedi
Martin J. Wainwright
Michael I. Jordan
Bin Yu
70
20
0
22 May 2020
Computationally efficient sparse clustering
Computationally efficient sparse clustering
Matthias Löffler
Alexander S. Wein
Afonso S. Bandeira
62
15
0
21 May 2020
Optimal estimation of high-dimensional location Gaussian mixtures
Optimal estimation of high-dimensional location Gaussian mixtures
Natalie Doss
Yihong Wu
Pengkun Yang
Harrison H. Zhou
70
22
0
14 Feb 2020
Cutoff for exact recovery of Gaussian mixture models
Cutoff for exact recovery of Gaussian mixture models
Xiaohui Chen
Yun Yang
45
20
0
05 Jan 2020
Sparse Density Estimation with Measurement Errors
Sparse Density Estimation with Measurement Errors
Xiaowei Yang
Huiming Zhang
Haoyu Wei
Shouzheng Zhang
72
3
0
14 Nov 2019
Iterative Algorithm for Discrete Structure Recovery
Iterative Algorithm for Discrete Structure Recovery
Chao Gao
A. Zhang
500
31
0
04 Nov 2019
Sharp optimal recovery in the two-component Gaussian Mixture Model
Sharp optimal recovery in the two-component Gaussian Mixture Model
M. Ndaoud
310
43
0
19 Dec 2018
1