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1408.2156
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Statistical guarantees for the EM algorithm: From population to sample-based analysis
9 August 2014
Sivaraman Balakrishnan
Martin J. Wainwright
Bin Yu
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Papers citing
"Statistical guarantees for the EM algorithm: From population to sample-based analysis"
50 / 265 papers shown
Distributed Banach-Picard Iteration: Application to Distributed EM and Distributed PCA
IEEE Transactions on Signal Processing (IEEE TSP), 2021
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Mário A. T. Figueiredo
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137
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20 Jun 2021
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Abishek Sankararaman
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A Wasserstein Minimax Framework for Mixed Linear Regression
International Conference on Machine Learning (ICML), 2021
Theo Diamandis
Yonina C. Eldar
Alireza Fallah
Farzan Farnia
Asuman Ozdaglar
183
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14 Jun 2021
From inexact optimization to learning via gradient concentration
Computational optimization and applications (COA), 2021
Bernhard Stankewitz
Nicole Mücke
Lorenzo Rosasco
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09 Jun 2021
LiMIIRL: Lightweight Multiple-Intent Inverse Reinforcement Learning
Aaron J. Snoswell
Surya P. N. Singh
N. Ye
184
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03 Jun 2021
Jointly Modeling and Clustering Tensors in High Dimensions
Operational Research (OR), 2021
Biao Cai
Jingfei Zhang
W. Sun
155
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15 Apr 2021
The computational asymptotics of Gaussian variational inference and the Laplace approximation
Statistics and computing (Stat Comput), 2021
Zuheng Xu
Trevor Campbell
373
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0
13 Apr 2021
High-Dimensional Differentially-Private EM Algorithm: Methods and Near-Optimal Statistical Guarantees
Zhe Zhang
Linjun Zhang
FedML
233
3
0
01 Apr 2021
The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures
Journal of machine learning research (JMLR), 2021
Nir Weinberger
Guy Bresler
FedML
161
8
0
29 Mar 2021
Large-Sample Properties of Blind Estimation of the Linear Discriminant Using Projection Pursuit
Electronic Journal of Statistics (EJS), 2021
Una Radojicic
K. Nordhausen
Joni Virta
130
7
0
08 Mar 2021
On the computational and statistical complexity of over-parameterized matrix sensing
Journal of machine learning research (JMLR), 2021
Jiacheng Zhuo
Jeongyeol Kwon
Nhat Ho
Constantine Caramanis
244
33
0
27 Jan 2021
The EM Perspective of Directional Mean Shift Algorithm
Yikun Zhang
Yen-Chi Chen
94
2
0
25 Jan 2021
Improved Convergence Guarantees for Learning Gaussian Mixture Models by EM and Gradient EM
Electronic Journal of Statistics (EJS), 2021
Nimrod Segol
B. Nadler
293
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0
03 Jan 2021
Spectral Methods for Data Science: A Statistical Perspective
Yuxin Chen
Yuejie Chi
Jianqing Fan
Cong Ma
513
201
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15 Dec 2020
Neural Contextual Bandits with Deep Representation and Shallow Exploration
International Conference on Learning Representations (ICLR), 2020
Pan Xu
Zheng Wen
Handong Zhao
Quanquan Gu
OffRL
178
83
0
03 Dec 2020
A Stochastic Path-Integrated Differential EstimatoR Expectation Maximization Algorithm
G. Fort
Eric Moulines
Hoi-To Wai
TPM
170
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0
30 Nov 2020
Towards Optimal Problem Dependent Generalization Error Bounds in Statistical Learning Theory
Mathematics of Operations Research (MOR), 2020
Yunbei Xu
A. Zeevi
453
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0
12 Nov 2020
Estimation, Confidence Intervals, and Large-Scale Hypotheses Testing for High-Dimensional Mixed Linear Regression
Linjun Zhang
Rong Ma
T. Tony Cai
Hongzhe Li
162
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0
06 Nov 2020
SGB: Stochastic Gradient Bound Method for Optimizing Partition Functions
Junchang Wang
A. Choromańska
149
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0
03 Nov 2020
Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Frederik Kunstner
Raunak Kumar
Mark Schmidt
509
32
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02 Nov 2020
Statistical optimality and stability of tangent transform algorithms in logit models
Journal of machine learning research (JMLR), 2020
I. Ghosh
A. Bhattacharya
D. Pati
237
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0
25 Oct 2020
Differentially Private (Gradient) Expectation Maximization Algorithm with Statistical Guarantees
Haiyan Zhao
Jiahao Ding
Lijie Hu
Zejun Xie
Miao Pan
Jinhui Xu
149
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22 Oct 2020
Distributed Learning of Finite Gaussian Mixtures
Journal of machine learning research (JMLR), 2020
Qiong Zhang
Jiahua Chen
413
10
0
20 Oct 2020
Robust High Dimensional Expectation Maximization Algorithm via Trimmed Hard Thresholding
Machine-mediated learning (ML), 2020
Haiyan Zhao
Xiangyu Guo
Shi Li
Jinhui Xu
191
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19 Oct 2020
Provable Hierarchical Imitation Learning via EM
Zhiyu Zhang
I. Paschalidis
171
18
0
07 Oct 2020
Local Minima Structures in Gaussian Mixture Models
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Yudong Chen
Dogyoon Song
Xumei Xi
Yuqian Zhang
291
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0
28 Sep 2020
Statistical Inference for High-Dimensional Vector Autoregression with Measurement Error
Statistica sinica (SS), 2020
Xiang Lyu
Jian Kang
Lexin Li
240
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0
17 Sep 2020
Online Robust and Adaptive Learning from Data Streams
Shintaro Fukushima
Atsushi Nitanda
Kenji Yamanishi
278
3
0
23 Jul 2020
From Symmetry to Geometry: Tractable Nonconvex Problems
Yuqian Zhang
Qing Qu
John N. Wright
347
48
0
14 Jul 2020
Model-based Clustering using Automatic Differentiation: Confronting Misspecification and High-Dimensional Data
bioRxiv (bioRxiv), 2019
Siva Rajesh Kasa
Vaibhav Rajan
130
0
0
08 Jul 2020
Sinkhorn EM: An Expectation-Maximization algorithm based on entropic optimal transport
Gonzalo E. Mena
Amin Nejatbakhsh
E. Varol
Jonathan Niles-Weed
OT
166
13
0
30 Jun 2020
Recovery of Sparse Signals from a Mixture of Linear Samples
A. Mazumdar
S. Pal
FedML
182
12
0
29 Jun 2020
Likelihood Maximization and Moment Matching in Low SNR Gaussian Mixture Models
A. Katsevich
Afonso S. Bandeira
114
22
0
26 Jun 2020
GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models
Farzan Farnia
William Wang
Subhro Das
Ali Jadbabaie
GAN
173
8
0
18 Jun 2020
Homomorphic Sensing of Subspace Arrangements
Liangzu Peng
M. Tsakiris
292
13
0
09 Jun 2020
An Efficient Framework for Clustered Federated Learning
Avishek Ghosh
Jichan Chung
Dong Yin
Kannan Ramchandran
FedML
379
1,079
0
07 Jun 2020
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Jeongyeol Kwon
Nhat Ho
Constantine Caramanis
228
41
0
04 Jun 2020
Instability, Computational Efficiency and Statistical Accuracy
Nhat Ho
K. Khamaru
Raaz Dwivedi
Martin J. Wainwright
Sai Li
Bin Yu
197
20
0
22 May 2020
Computationally efficient sparse clustering
Matthias Löffler
Alexander S. Wein
Afonso S. Bandeira
290
18
0
21 May 2020
Reducibility and Statistical-Computational Gaps from Secret Leakage
Matthew Brennan
Guy Bresler
334
100
0
16 May 2020
Outlier-Robust Clustering of Non-Spherical Mixtures
Ainesh Bakshi
Pravesh Kothari
347
34
0
06 May 2020
Alternating Minimization Converges Super-Linearly for Mixed Linear Regression
Avishek Ghosh
Kannan Ramchandran
235
19
0
23 Apr 2020
Convex Nonparanormal Regression
Yonatan Woodbridge
G. Elidan
A. Wiesel
UQCV
95
0
0
21 Apr 2020
Efficient Clustering for Stretched Mixtures: Landscape and Optimality
Neural Information Processing Systems (NeurIPS), 2020
Kaizheng Wang
Yuling Yan
Mateo Díaz
241
14
0
22 Mar 2020
A Robust Functional EM Algorithm for Incomplete Panel Count Data
Alexander Moreno
Zhenke Wu
Jamie Yap
D. Wetter
Cho Lam
Inbal Nahum-Shani
Walter Dempsey
James M. Rehg
119
0
0
02 Mar 2020
Partially Observed Dynamic Tensor Response Regression
Journal of the American Statistical Association (JASA), 2020
Jie Zhou
W. Sun
Jingfei Zhang
Lexin Li
228
29
0
22 Feb 2020
Gaussian Mixture Reduction with Composite Transportation Divergence
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Qiong Zhang
Archer Gong Zhang
Jiahua Chen
445
5
0
19 Feb 2020
Structures of Spurious Local Minima in
k
k
k
-means
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Wei Qian
Yuqian Zhang
Yudong Chen
223
15
0
16 Feb 2020
Solution manifold and Its Statistical Applications
Journal of statistical physics (J. Stat. Phys.), 2018
Swee Hong Chan
203
7
0
13 Feb 2020
The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians
Jeongyeol Kwon
Constantine Caramanis
259
5
0
02 Feb 2020
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