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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

ArXiv (abs)PDF HTML

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

50 / 265 papers shown

Title
Cutoff for exact recovery of Gaussian mixture modelsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020 Xiaohui Chen Yun Yang 248 24 0 05 Jan 2020
Universal InferenceProceedings of the National Academy of Sciences of the United States of America (PNAS), 2019 Larry A. Wasserman Aaditya Ramdas Sivaraman Balakrishnan 281 178 0 24 Dec 2019
Learning Mixtures of Linear Regressions in Subexponential Time via Fourier MomentsSymposium on the Theory of Computing (STOC), 2019 Sitan Chen Haibin Zhang Zhao Song 142 41 0 16 Dec 2019
Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing Wenlong Mou Nhat Ho Martin J. Wainwright Peter L. Bartlett Sai Li 166 9 0 11 Dec 2019
Adversarially Robust Low Dimensional RepresentationsAnnual Conference Computational Learning Theory (COLT), 2019 Pranjal Awasthi Vaggos Chatziafratis Xue Chen Aravindan Vijayaraghavan AAML OOD 286 12 0 29 Nov 2019
Sparse Density Estimation with Measurement Errors Xiaowei Yang Huiming Zhang Haoyu Wei Shouzheng Zhang 377 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 126 3 0 08 Nov 2019
Iterative Algorithm for Discrete Structure RecoveryAnnals of Statistics (Ann. Stat.), 2019 Chao Gao A. Zhang 860 33 0 04 Nov 2019
On the Global Convergence of (Fast) Incremental Expectation Maximization MethodsNeural Information Processing Systems (NeurIPS), 2019 Belhal Karimi Hoi-To Wai Eric Moulines M. Lavielle 111 29 0 28 Oct 2019
Gaussian Mixture Clustering Using Relative Tests of Fit Purvasha Chakravarti Sivaraman Balakrishnan Larry A. Wasserman 134 10 0 07 Oct 2019
A Diffusion Process Perspective on Posterior Contraction Rates for ParametersSIAM Journal on Mathematics of Data Science (SIMODS), 2019 Wenlong Mou Nhat Ho Martin J. Wainwright Peter L. Bartlett Sai Li 206 16 0 03 Sep 2019
$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 $O(\sqrt{n})$ iterationsMathematical Statistics and Learning (MSL), 2019 Yihong Wu Harrison H. Zhou 362 48 0 28 Aug 2019
ZeroER: Entity Resolution using Zero Labeled Examples Renzhi Wu Sanya Chaba Saurabh Sawlani Xu Chu Saravanan Thirumuruganathan 225 102 0 16 Aug 2019
Path Length Bounds for Gradient Descent and FlowJournal of machine learning research (JMLR), 2019 Chirag Gupta Sivaraman Balakrishnan Aaditya Ramdas 237 15 0 02 Aug 2019
A Theoretical Case Study of Structured Variational Inference for Community DetectionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Mingzhang Yin Y. X. R. Wang Purnamrita Sarkar 207 8 0 29 Jul 2019
SuperMix: Sparse Regularization for Mixtures Yohann De Castro S. Gadat C. Marteau Cathy Maugis 124 0 0 23 Jul 2019
Comparing EM with GD in Mixture Models of Two ComponentsConference on Uncertainty in Artificial Intelligence (UAI), 2019 Guojun Zhang Pascal Poupart George Trimponias 183 1 0 08 Jul 2019
Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation Avishek Ghosh A. Pananjady Adityanand Guntuboyina Kannan Ramchandran 160 27 0 21 Jun 2019
A Survey of Optimization Methods from a Machine Learning PerspectiveIEEE Transactions on Cybernetics (IEEE Trans. Cybern.), 2019 Shiliang Sun Zehui Cao Han Zhu Jing Zhao 181 618 0 17 Jun 2019
Global Convergence of Least Squares EM for Demixing Two Log-Concave DensitiesNeural Information Processing Systems (NeurIPS), 2019 Wei Qian Yuqian Zhang Yudong Chen 138 10 0 16 Jun 2019
Learning Mixtures of Graphs from Epidemic CascadesInternational Conference on Machine Learning (ICML), 2019 Jessica Hoffmann Soumya Basu Surbhi Goel Constantine Caramanis 158 5 0 14 Jun 2019
Learning in Gated Neural NetworksInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Ashok Vardhan Makkuva Sewoong Oh Sreeram Kannan Pramod Viswanath 167 13 0 06 Jun 2019
EM Converges for a Mixture of Many Linear RegressionsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Jeongyeol Kwon Constantine Caramanis 138 41 0 28 May 2019
A view of Estimation of Distribution Algorithms through the lens of Expectation-Maximization David H. Brookes A. Busia Clara Fannjiang Kevin Patrick Murphy Jennifer Listgarten 495 24 0 24 May 2019
List-Decodable Linear RegressionNeural Information Processing Systems (NeurIPS), 2019 Sushrut Karmalkar Adam R. Klivans Pravesh Kothari 233 79 0 14 May 2019
Sparse Tensor Additive Regression Botao Hao Boxiang Wang Pengyuan Wang Jingfei Zhang Jian Yang W. Sun MedIm 335 29 0 31 Mar 2019
Convergence of Parameter Estimates for Regularized Mixed Linear Regression ModelsIEEE Conference on Decision and Control (CDC), 2019 Taiyao Wang I. Paschalidis 878 7 0 21 Mar 2019
Analysis of a Generalized Expectation-Maximization Algorithm for Gaussian Mixture Models: A Control Systems PerspectiveInternational Journal of Control (IJC), 2019 Sarthak Chatterjee O. Romero S. Pequito 179 5 0 03 Mar 2019
Learning rates for Gaussian mixtures under group invariance Victor-Emmanuel Brunel 120 0 0 28 Feb 2019
On the Analysis of EM for truncated mixtures of two Gaussians Sai Ganesh Nagarajan Ioannis Panageas 231 15 0 19 Feb 2019
Iterative Least Trimmed Squares for Mixed Linear RegressionNeural Information Processing Systems (NeurIPS), 2019 Yanyao Shen Sujay Sanghavi 219 25 0 10 Feb 2019
Non-asymptotic Analysis of Biased Stochastic Approximation SchemeAnnual Conference Computational Learning Theory (COLT), 2019 Belhal Karimi B. Miasojedow Eric Moulines Hoi-To Wai 221 93 0 02 Feb 2019
Sharp Analysis of Expectation-Maximization for Weakly Identifiable ModelsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Raaz Dwivedi Nhat Ho K. Khamaru Martin J. Wainwright Sai Li Bin Yu 316 38 0 01 Feb 2019
High Dimensional Robust $M$ -Estimation: Arbitrary Corruption and Heavy Tails Liu Liu Tianyang Li Constantine Caramanis 187 14 0 24 Jan 2019
Learning with Bad Training Data via Iterative Trimmed Loss Minimization Yanyao Shen Sujay Sanghavi FedML 140 4 0 28 Oct 2018
Benefits of over-parameterization with EM Ji Xu Daniel J. Hsu A. Maleki 377 31 0 26 Oct 2018
Global Convergence of EM Algorithm for Mixtures of Two Component Linear Regression Jeongyeol Kwon Wei Qian Constantine Caramanis Yudong Chen Damek Davis 335 58 0 12 Oct 2018
Statistical Convergence of the EM Algorithm on Gaussian Mixture Models Ruofei Zhao Yuanzhi Li Yuekai Sun 131 51 0 09 Oct 2018
Singularity, Misspecification, and the Convergence Rate of EM Raaz Dwivedi Nhat Ho K. Khamaru Sai Li Martin J. Wainwright Bin Yu 217 69 0 01 Oct 2018
On the Behavior of the Expectation-Maximization Algorithm for Mixture Models Babak Barazandeh Meisam Razaviyayn 103 19 0 24 Sep 2018
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes C. J. Li Zhaoran Wang Han Liu DiffM 202 21 0 29 Aug 2018
Network Inference from Temporal-Dependent Grouped Observations Yunpeng Zhao 118 2 0 25 Aug 2018
Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval Jianqing Fan Han Liu Zhaoran Wang Zhuoran Yang 189 22 0 21 Aug 2018
Optimal estimation of Gaussian mixtures via denoised method of momentsAnnals of Statistics (Ann. Stat.), 2018 Yihong Wu Pengkun Yang 269 82 0 19 Jul 2018
Statistical Inference with Local Optima Yen-Chi Chen 145 9 0 12 Jul 2018
A Hierarchical Bayesian Linear Regression Model with Local Features for Stochastic Dynamics Approximation Behnoosh Parsa K. Rajasekaran Franziska Meier A. Banerjee 102 5 0 11 Jul 2018
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables A. Choromańska Benjamin Cowen Yara Rizk Ronny Luss Mattia Rigotti ... Brian Kingsbury Paolo Diachille V. Gurev Ravi Tejwani Djallel Bouneffouf 318 57 0 24 Jun 2018
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett FedML 341 103 0 14 Jun 2018
High Dimensional Robust Sparse Regression Liu Liu Yanyao Shen Tianyang Li Constantine Caramanis 299 74 0 29 May 2018
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model Kwangjun Ahn Kangwook Lee Changho Suh 184 69 0 23 May 2018

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

9 August 2014

Sivaraman Balakrishnan

Martin J. Wainwright

Bin Yu

ArXiv (abs)PDF HTML

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

50 / 265 papers shown

Title
Cutoff for exact recovery of Gaussian mixture modelsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020 Xiaohui Chen Yun Yang 248 24 0 05 Jan 2020
Universal InferenceProceedings of the National Academy of Sciences of the United States of America (PNAS), 2019 Larry A. Wasserman Aaditya Ramdas Sivaraman Balakrishnan 281 178 0 24 Dec 2019
Learning Mixtures of Linear Regressions in Subexponential Time via Fourier MomentsSymposium on the Theory of Computing (STOC), 2019 Sitan Chen Haibin Zhang Zhao Song 142 41 0 16 Dec 2019
Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing Wenlong Mou Nhat Ho Martin J. Wainwright Peter L. Bartlett Sai Li 166 9 0 11 Dec 2019
Adversarially Robust Low Dimensional RepresentationsAnnual Conference Computational Learning Theory (COLT), 2019 Pranjal Awasthi Vaggos Chatziafratis Xue Chen Aravindan Vijayaraghavan AAML OOD 286 12 0 29 Nov 2019
Sparse Density Estimation with Measurement Errors Xiaowei Yang Huiming Zhang Haoyu Wei Shouzheng Zhang 377 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 126 3 0 08 Nov 2019
Iterative Algorithm for Discrete Structure RecoveryAnnals of Statistics (Ann. Stat.), 2019 Chao Gao A. Zhang 860 33 0 04 Nov 2019
On the Global Convergence of (Fast) Incremental Expectation Maximization MethodsNeural Information Processing Systems (NeurIPS), 2019 Belhal Karimi Hoi-To Wai Eric Moulines M. Lavielle 111 29 0 28 Oct 2019
Gaussian Mixture Clustering Using Relative Tests of Fit Purvasha Chakravarti Sivaraman Balakrishnan Larry A. Wasserman 134 10 0 07 Oct 2019
A Diffusion Process Perspective on Posterior Contraction Rates for ParametersSIAM Journal on Mathematics of Data Science (SIMODS), 2019 Wenlong Mou Nhat Ho Martin J. Wainwright Peter L. Bartlett Sai Li 206 16 0 03 Sep 2019
$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 $O(\sqrt{n})$ iterationsMathematical Statistics and Learning (MSL), 2019 Yihong Wu Harrison H. Zhou 362 48 0 28 Aug 2019
ZeroER: Entity Resolution using Zero Labeled Examples Renzhi Wu Sanya Chaba Saurabh Sawlani Xu Chu Saravanan Thirumuruganathan 225 102 0 16 Aug 2019
Path Length Bounds for Gradient Descent and FlowJournal of machine learning research (JMLR), 2019 Chirag Gupta Sivaraman Balakrishnan Aaditya Ramdas 237 15 0 02 Aug 2019
A Theoretical Case Study of Structured Variational Inference for Community DetectionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Mingzhang Yin Y. X. R. Wang Purnamrita Sarkar 207 8 0 29 Jul 2019
SuperMix: Sparse Regularization for Mixtures Yohann De Castro S. Gadat C. Marteau Cathy Maugis 124 0 0 23 Jul 2019
Comparing EM with GD in Mixture Models of Two ComponentsConference on Uncertainty in Artificial Intelligence (UAI), 2019 Guojun Zhang Pascal Poupart George Trimponias 183 1 0 08 Jul 2019
Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation Avishek Ghosh A. Pananjady Adityanand Guntuboyina Kannan Ramchandran 160 27 0 21 Jun 2019
A Survey of Optimization Methods from a Machine Learning PerspectiveIEEE Transactions on Cybernetics (IEEE Trans. Cybern.), 2019 Shiliang Sun Zehui Cao Han Zhu Jing Zhao 181 618 0 17 Jun 2019
Global Convergence of Least Squares EM for Demixing Two Log-Concave DensitiesNeural Information Processing Systems (NeurIPS), 2019 Wei Qian Yuqian Zhang Yudong Chen 138 10 0 16 Jun 2019
Learning Mixtures of Graphs from Epidemic CascadesInternational Conference on Machine Learning (ICML), 2019 Jessica Hoffmann Soumya Basu Surbhi Goel Constantine Caramanis 158 5 0 14 Jun 2019
Learning in Gated Neural NetworksInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Ashok Vardhan Makkuva Sewoong Oh Sreeram Kannan Pramod Viswanath 167 13 0 06 Jun 2019
EM Converges for a Mixture of Many Linear RegressionsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Jeongyeol Kwon Constantine Caramanis 138 41 0 28 May 2019
A view of Estimation of Distribution Algorithms through the lens of Expectation-Maximization David H. Brookes A. Busia Clara Fannjiang Kevin Patrick Murphy Jennifer Listgarten 495 24 0 24 May 2019
List-Decodable Linear RegressionNeural Information Processing Systems (NeurIPS), 2019 Sushrut Karmalkar Adam R. Klivans Pravesh Kothari 233 79 0 14 May 2019
Sparse Tensor Additive Regression Botao Hao Boxiang Wang Pengyuan Wang Jingfei Zhang Jian Yang W. Sun MedIm 335 29 0 31 Mar 2019
Convergence of Parameter Estimates for Regularized Mixed Linear Regression ModelsIEEE Conference on Decision and Control (CDC), 2019 Taiyao Wang I. Paschalidis 878 7 0 21 Mar 2019
Analysis of a Generalized Expectation-Maximization Algorithm for Gaussian Mixture Models: A Control Systems PerspectiveInternational Journal of Control (IJC), 2019 Sarthak Chatterjee O. Romero S. Pequito 179 5 0 03 Mar 2019
Learning rates for Gaussian mixtures under group invariance Victor-Emmanuel Brunel 120 0 0 28 Feb 2019
On the Analysis of EM for truncated mixtures of two Gaussians Sai Ganesh Nagarajan Ioannis Panageas 231 15 0 19 Feb 2019
Iterative Least Trimmed Squares for Mixed Linear RegressionNeural Information Processing Systems (NeurIPS), 2019 Yanyao Shen Sujay Sanghavi 219 25 0 10 Feb 2019
Non-asymptotic Analysis of Biased Stochastic Approximation SchemeAnnual Conference Computational Learning Theory (COLT), 2019 Belhal Karimi B. Miasojedow Eric Moulines Hoi-To Wai 221 93 0 02 Feb 2019
Sharp Analysis of Expectation-Maximization for Weakly Identifiable ModelsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Raaz Dwivedi Nhat Ho K. Khamaru Martin J. Wainwright Sai Li Bin Yu 316 38 0 01 Feb 2019
High Dimensional Robust $M$ -Estimation: Arbitrary Corruption and Heavy Tails Liu Liu Tianyang Li Constantine Caramanis 187 14 0 24 Jan 2019
Learning with Bad Training Data via Iterative Trimmed Loss Minimization Yanyao Shen Sujay Sanghavi FedML 140 4 0 28 Oct 2018
Benefits of over-parameterization with EM Ji Xu Daniel J. Hsu A. Maleki 377 31 0 26 Oct 2018
Global Convergence of EM Algorithm for Mixtures of Two Component Linear Regression Jeongyeol Kwon Wei Qian Constantine Caramanis Yudong Chen Damek Davis 335 58 0 12 Oct 2018
Statistical Convergence of the EM Algorithm on Gaussian Mixture Models Ruofei Zhao Yuanzhi Li Yuekai Sun 131 51 0 09 Oct 2018
Singularity, Misspecification, and the Convergence Rate of EM Raaz Dwivedi Nhat Ho K. Khamaru Sai Li Martin J. Wainwright Bin Yu 217 69 0 01 Oct 2018
On the Behavior of the Expectation-Maximization Algorithm for Mixture Models Babak Barazandeh Meisam Razaviyayn 103 19 0 24 Sep 2018
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes C. J. Li Zhaoran Wang Han Liu DiffM 202 21 0 29 Aug 2018
Network Inference from Temporal-Dependent Grouped Observations Yunpeng Zhao 118 2 0 25 Aug 2018
Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval Jianqing Fan Han Liu Zhaoran Wang Zhuoran Yang 189 22 0 21 Aug 2018
Optimal estimation of Gaussian mixtures via denoised method of momentsAnnals of Statistics (Ann. Stat.), 2018 Yihong Wu Pengkun Yang 269 82 0 19 Jul 2018
Statistical Inference with Local Optima Yen-Chi Chen 145 9 0 12 Jul 2018
A Hierarchical Bayesian Linear Regression Model with Local Features for Stochastic Dynamics Approximation Behnoosh Parsa K. Rajasekaran Franziska Meier A. Banerjee 102 5 0 11 Jul 2018
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables A. Choromańska Benjamin Cowen Yara Rizk Ronny Luss Mattia Rigotti ... Brian Kingsbury Paolo Diachille V. Gurev Ravi Tejwani Djallel Bouneffouf 318 57 0 24 Jun 2018
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett FedML 341 103 0 14 Jun 2018
High Dimensional Robust Sparse Regression Liu Liu Yanyao Shen Tianyang Li Constantine Caramanis 299 74 0 29 May 2018
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model Kwangjun Ahn Kangwook Lee Changho Suh 184 69 0 23 May 2018