Statistical guarantees for the EM algorithm: From population to sample-based analysis

9 August 2014

Papers citing "Statistical guarantees for the EM algorithm: From population to sample-based analysis"

50 / 156 papers shown

Title
Improved Convergence Guarantees for Learning Gaussian Mixture Models by EM and Gradient EM Nimrod Segol B. Nadler 19 11 0 03 Jan 2021
Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 14 165 0 15 Dec 2020
Neural Contextual Bandits with Deep Representation and Shallow Exploration Pan Xu Zheng Wen Handong Zhao Quanquan Gu OffRL 10 72 0 03 Dec 2020
A Stochastic Path-Integrated Differential EstimatoR Expectation Maximization Algorithm G. Fort Eric Moulines Hoi-To Wai TPM 6 7 0 30 Nov 2020
Towards Optimal Problem Dependent Generalization Error Bounds in Statistical Learning Theory Yunbei Xu A. Zeevi 8 16 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 28 12 0 06 Nov 2020
SGB: Stochastic Gradient Bound Method for Optimizing Partition Functions Junchang Wang A. Choromańska 6 0 0 03 Nov 2020
Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent Frederik Kunstner Raunak Kumar Mark W. Schmidt 14 21 0 02 Nov 2020
Statistical optimality and stability of tangent transform algorithms in logit models I. Ghosh A. Bhattacharya D. Pati 6 3 0 25 Oct 2020
Differentially Private (Gradient) Expectation Maximization Algorithm with Statistical Guarantees Di Wang Jiahao Ding Lijie Hu Zejun Xie Miao Pan Jinhui Xu 4 0 0 22 Oct 2020
Distributed Learning of Finite Gaussian Mixtures Qiong Zhang Jiahua Chen 34 8 0 20 Oct 2020
Robust High Dimensional Expectation Maximization Algorithm via Trimmed Hard Thresholding Di Wang Xiangyu Guo Shi Li Jinhui Xu 13 3 0 19 Oct 2020
Provable Hierarchical Imitation Learning via EM Zhiyu Zhang I. Paschalidis 19 17 0 07 Oct 2020
Local Minima Structures in Gaussian Mixture Models Yudong Chen Dogyoon Song Xumei Xi Yuqian Zhang 6 2 0 28 Sep 2020
Statistical Inference for High-Dimensional Vector Autoregression with Measurement Error Xiang Lyu Jian Kang Lexin Li 8 1 0 17 Sep 2020
Online Robust and Adaptive Learning from Data Streams Shintaro Fukushima Atsushi Nitanda Kenji Yamanishi 6 3 0 23 Jul 2020
From Symmetry to Geometry: Tractable Nonconvex Problems Yuqian Zhang Qing Qu John N. Wright 26 43 0 14 Jul 2020
Model-based Clustering using Automatic Differentiation: Confronting Misspecification and High-Dimensional Data Siva Rajesh Kasa Vaibhav Rajan 7 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 11 12 0 30 Jun 2020
Recovery of Sparse Signals from a Mixture of Linear Samples A. Mazumdar S. Pal FedML 8 12 0 29 Jun 2020
Likelihood Maximization and Moment Matching in Low SNR Gaussian Mixture Models A. Katsevich Afonso S. Bandeira 9 17 0 26 Jun 2020
GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models Farzan Farnia William Wang Subhro Das Ali Jadbabaie GAN 8 7 0 18 Jun 2020
Homomorphic Sensing of Subspace Arrangements Liangzu Peng M. Tsakiris 11 13 0 09 Jun 2020
An Efficient Framework for Clustered Federated Learning Avishek Ghosh Jichan Chung Dong Yin K. Ramchandran FedML 10 832 0 07 Jun 2020
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression Jeongyeol Kwon Nhat Ho C. Caramanis 6 39 0 04 Jun 2020
Instability, Computational Efficiency and Statistical Accuracy Nhat Ho K. Khamaru Raaz Dwivedi Martin J. Wainwright Michael I. Jordan Bin Yu 6 20 0 22 May 2020
Computationally efficient sparse clustering Matthias Löffler Alexander S. Wein Afonso S. Bandeira 22 14 0 21 May 2020
Reducibility and Statistical-Computational Gaps from Secret Leakage Matthew Brennan Guy Bresler 19 85 0 16 May 2020
Outlier-Robust Clustering of Non-Spherical Mixtures Ainesh Bakshi Pravesh Kothari 8 31 0 06 May 2020
Alternating Minimization Converges Super-Linearly for Mixed Linear Regression Avishek Ghosh K. Ramchandran 9 19 0 23 Apr 2020
Convex Nonparanormal Regression Yonatan Woodbridge G. Elidan A. Wiesel UQCV 6 0 0 21 Apr 2020
Efficient Clustering for Stretched Mixtures: Landscape and Optimality Kaizheng Wang Yuling Yan Mateo Díaz 9 13 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 14 0 0 02 Mar 2020
Partially Observed Dynamic Tensor Response Regression Jie Zhou W. Sun Jingfei Zhang Lexin Li 15 22 0 22 Feb 2020
Gaussian Mixture Reduction with Composite Transportation Divergence Qiong Zhang Archer Gong Zhang Jiahua Chen 10 2 0 19 Feb 2020
Structures of Spurious Local Minima in $k$ -means Wei Qian Yuqian Zhang Yudong Chen 19 14 0 16 Feb 2020
The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians Jeongyeol Kwon C. Caramanis 11 5 0 02 Feb 2020
Cutoff for exact recovery of Gaussian mixture models Xiaohui Chen Yun Yang 12 20 0 05 Jan 2020
Universal Inference Larry A. Wasserman Aaditya Ramdas Sivaraman Balakrishnan 19 144 0 24 Dec 2019
Learning Mixtures of Linear Regressions in Subexponential Time via Fourier Moments Sitan Chen J. Li Zhao-quan Song 13 39 0 16 Dec 2019
Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing Wenlong Mou Nhat Ho Martin J. Wainwright Peter L. Bartlett Michael I. Jordan 9 8 0 11 Dec 2019
Adversarially Robust Low Dimensional Representations Pranjal Awasthi Vaggos Chatziafratis Xue Chen Aravindan Vijayaraghavan AAML OOD 16 12 0 29 Nov 2019
Sparse Density Estimation with Measurement Errors Xiaowei Yang Huiming Zhang Haoyu Wei Shouzheng Zhang 8 3 0 14 Nov 2019
MAP Clustering under the Gaussian Mixture Model via Mixed Integer Nonlinear Optimization Patrick Flaherty Pitchaya Wiratchotisatian John A. Lee Zhou Tang Andrew C. Trapp 11 3 0 08 Nov 2019
Iterative Algorithm for Discrete Structure Recovery Chao Gao A. Zhang 17 30 0 04 Nov 2019
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods Belhal Karimi Hoi-To Wai Eric Moulines M. Lavielle 16 27 0 28 Oct 2019
Gaussian Mixture Clustering Using Relative Tests of Fit Purvasha Chakravarti Sivaraman Balakrishnan Larry A. Wasserman 16 9 0 07 Oct 2019
ZeroER: Entity Resolution using Zero Labeled Examples Renzhi Wu Sanya Chaba Saurabh Sawlani Xu Chu Saravanan Thirumuruganathan 13 90 0 16 Aug 2019
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model Kwangjun Ahn Kangwook Lee Changho Suh 13 63 0 23 May 2018
Robust Estimation via Robust Gradient Estimation Adarsh Prasad A. Suggala Sivaraman Balakrishnan Pradeep Ravikumar 20 219 0 19 Feb 2018