Rong Ge

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All published works

Action	Title	Year	Authors
+ PDF Chat	ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods	2024	Roy Xie Junlin Wang Ruomin Huang Minxing Zhang Rong Ge Jian Pei Neil Zhenqiang Gong Bhuwan Dhingra
+ PDF Chat	How Does Gradient Descent Learn Features -- A Local Analysis for Regularized Two-Layer Neural Networks	2024	Mo Zhou Rong Ge
+	Shared Virtual Memory: Its Design and Performance Implications for Diverse Applications	2024	Bennett Cooper Tom Scogland Rong Ge
+ PDF Chat	Linear Transformers are Versatile In-Context Learners	2024	Max Vladymyrov Johannes von Oswald M. Sandler Rong Ge
+ PDF Chat	Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input	2024	Ziang Chen Rong Ge
+ PDF Chat	For Better or For Worse? Learning Minimum Variance Features With Label Augmentation	2024	Muthu Chidambaram Rong Ge
+ PDF Chat	Transfer-learning-based Autotuning using Gaussian Copula	2023	Thomas Randall Jaehoon Koo Brice Videau Michael Kruse Xingfu Wu Paul Hovland Mary Hall Rong Ge Prasanna Balaprakash
+	Performance Implication of Tensor Irregularity and Optimization for Distributed Tensor Decomposition	2023	Zheng Miao Jon C. Calhoun Rong Ge Jiajia Li
+	Do Transformers Parse while Predicting the Masked Word?	2023	Haoyu Zhao Abhishek Panigrahi Rong Ge Sanjeev Arora
+	Depth Separation with Multilayer Mean-Field Networks	2023	Yunwei Ren Mo Zhou Rong Ge
+	Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models	2023	Alex Damian Eshaan Nichani Rong Ge Jason D. Lee
+	On the Limitations of Temperature Scaling for Distributions with Overlaps	2023	Muthu Chidambaram Rong Ge
+	The Role of Linguistic Priors in Measuring Compositional Generalization of Vision-Language Models	2023	Chen-Wei Wu Li Erran Li Stefano Ermon Patrick Haffner Rong Ge Zaiwei Zhang
+ PDF Chat	Do Transformers Parse while Predicting the Masked Word?	2023	Haoyu Zhao Abhishek Panigrahi Rong Ge Sanjeev Arora
+	BALA-CPD: BALanced and Asynchronous Distributed Tensor Decomposition	2022	Zheng Miao Jiajia Li Jon C. Calhoun Rong Ge
+	Understanding The Robustness of Self-supervised Learning Through Topic Modeling	2022	Zeping Luo Cindy Weng Shiyou Wu Mo Zhou Rong Ge
+	Customizing ML Predictions for Online Algorithms	2022	Keerti Anand Rong Ge Debmalya Panigrahi
+	A Regression Approach to Learning-Augmented Online Algorithms	2022	Keerti Anand Rong Ge Amit Kumar Debmalya Panigrahi
+	Plateau in Monotonic Linear Interpolation -- A "Biased" View of Loss Landscape for Deep Networks	2022	Xiang Wang Annie N. Wang Mo Zhou Rong Ge
+	Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup	2022	Muthu Chidambaram Xiang Wang Chenwei Wu Rong Ge
+	Online Algorithms with Multiple Predictions	2022	Keerti Anand Rong Ge Amit Kumar Debmalya Panigrahi
+	Understanding Deflation Process in Over-parametrized Tensor Decomposition	2021	Rong Ge Yunwei Ren Xiang Wang Mo Zhou
+	FULL-W2V	2021	Thomas Randall Tyler Allen Rong Ge
+	Understanding Deflation Process in Over-parametrized Tensor Decomposition	2021	Rong Ge Yunwei Ren Xiang Wang Mo Zhou
+ PDF Chat	Extracting Latent State Representations with Linear Dynamics from Rich Observations	2020	Abraham Frandsen Rong Ge
+ PDF Chat	Optimization landscape of Tucker decomposition	2020	Abraham Frandsen Rong Ge
+	Energy-Aware DNN Graph Optimization	2020	Yu Wang Rong Ge Shuang Qiu
+	Extracting Latent State Representations with Linear Dynamics from Rich Observations	2020	Abraham Frandsen Rong Ge
+	Guarantees for Tuning the Step Size using a Learning-to-Learn Approach	2020	Xiang Wang Shuai Yuan Chenwei Wu Rong Ge
+	Beyond Lazy Training for Over-parameterized Tensor Decomposition	2020	Xiang Wang Chenwei Wu Jason D. Lee Tengyu Ma Rong Ge
+	The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure.	2019	Rong Ge Sham M. Kakade Rahul Kidambi Praneeth Netrapalli
+	Stochastic Gradient Descent Escapes Saddle Points Efficiently.	2019	Chi Jin Praneeth Netrapalli Rong Ge Sham M. Kakade Michael I. Jordan
+	Understanding Composition of Word Embeddings via Tensor Decomposition	2019	Abraham Frandsen Rong Ge
+	A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm	2019	Chi Jin Praneeth Netrapalli Rong Ge Sham M. Kakade Michael I. Jordan
+ PDF Chat	High-Dimensional Robust Mean Estimation in Nearly-Linear Time	2019	Yu Cheng Ilias Diakonikolas Rong Ge
+	Understanding Composition of Word Embeddings via Tensor Decomposition.	2019	Abraham Frandsen Rong Ge
+ PDF Chat	Spectral Learning on Matrices and Tensors	2019	Majid Janzamin Rong Ge Jean Kossaifi Anima Anandkumar
+	The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares	2019	Rong Ge Sham M. Kakade Rahul Kidambi Praneeth Netrapalli
+ PDF Chat	Spectral Learning on Matrices and Tensors	2019	Majid Janzamin Rong Ge Jean Kossaifi Anima Anandkumar
+	Learning Two-Layer Neural Networks with Symmetric Inputs	2018	Rong Ge Rohith Kuditipudi Zhize Li Xiang Wang
+	Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator	2018	Maryam Fazel Rong Ge Sham M. Kakade Mehran Mesbahi
+	Simulated Tempering Langevin Monte Carlo II: An Improved Proof using Soft Markov Chain Decomposition	2018	Rong Ge Holden Lee Andrej Risteski
+	On the Local Minima of the Empirical Risk	2018	Chi Jin Lydia T. Liu Rong Ge Michael I. Jordan
+	Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo	2018	Holden Lee Andrej Risteski Rong Ge
+	High-Dimensional Robust Mean Estimation in Nearly-Linear Time	2018	Yu Cheng Ilias Diakonikolas Rong Ge
+	Online Service with Delay	2017	Yossi Azar Arun Ganesh Rong Ge Debmalya Panigrahi
+	Analyzing tensor power method dynamics in overcomplete regime	2017	Animashree Anandkumar Rong Ge Majid Janzamin
+	Analyzing Tensor Power Method Dynamics in Overcomplete Regime - eScholarship	2017	Animashree Anandkumar Rong Ge Majid Janzamin
+	Online Service with Delay	2017	Yossi Azar Arun Ganesh Rong Ge Debmalya Panigrahi
+	Homotopy Method for Tensor Principal Component Analysis.	2016	Anima Anandkumar Yuan Deng Rong Ge Hossein Mobahi
+	Efficient approaches for escaping higher order saddle points in non-convex optimization	2016	Animashree Anandkumar Rong Ge
+	DynIMS: A Dynamic Memory Controller for In-memory Storage on HPC Systems	2016	Pengfei Xuan Feng Luo Rong Ge Pradip K. Srimani
+	Provable learning of Noisy-or Networks	2016	Sanjeev Arora Rong Ge Tengyu Ma Andrej Risteski
+ PDF Chat	Minimal Realization Problems for Hidden Markov Models	2015	Qingqing Huang Rong Ge Sham M. Kakade Munther A. Dahleh
+ PDF Chat	Big data analytics on traditional HPC infrastructure using two-level storage	2015	Pengfei Xuan Jeffrey Denton Pradip K. Srimani Rong Ge Feng Luo
+	Learning Overcomplete Latent Variable Models through Tensor Methods	2015	Animashree Anandkumar Rong Ge Majid Janzamin
+	Competing with the Empirical Risk Minimizer in a Single Pass	2015	Roy Frostig Rong Ge Sham M. Kakade Aaron Sidford
+ PDF Chat	Learning Mixtures of Gaussians in High Dimensions	2015	Rong Ge Qingqing Huang Sham M. Kakade
+	Decomposing Overcomplete 3rd Order Tensors using Sum-of-Squares Algorithms	2015	Rong Ge Tengyu Ma
+	Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition	2015	Rong Ge Furong Huang Chi Jin Yuan Yang
+	Intersecting Faces: Non-negative Matrix Factorization With New Guarantees	2015	Rong Ge James Zou
+	Decomposing Overcomplete 3rd Order Tensors using Sum-of-Squares Algorithms	2015	Rong Ge Tengyu Ma
+	Tensor Decompositions for Learning Latent Variable Models (A Survey for ALT)	2015	Anima Anandkumar Rong Ge Daniel Hsu Sham M. Kakade Matus Telgarsky
+	Learning Mixtures of Gaussians in High Dimensions	2015	Rong Ge Qingqing Huang Sham M. Kakade
+	Rich Component Analysis	2015	Rong Ge James Zou
+	Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition	2015	Rong Ge Furong Huang Chi Jin Yuan Yang
+	Analyzing Tensor Power Method Dynamics: Applications to Learning Overcomplete Latent Variable Models.	2014	Anima Anandkumar Rong Ge Majid Janzamin
+	Analyzing Tensor Power Method Dynamics in Overcomplete Regime	2014	Anima Anandkumar Rong Ge Majid Janzamin
+	Minimal realization problem for Hidden Markov Models	2014	Qingqing Huang Rong Ge Sham M. Kakade Munther A. Dahleh
+	Provable Learning of Overcomplete Latent Variable Models: Semi-supervised and Unsupervised Settings.	2014	Animashree Anandkumar Rong Ge Majid Janzamin
+	Sample Complexity Analysis for Learning Overcomplete Latent Variable Models through Tensor Methods	2014	Animashree Anandkumar Rong Ge Majid Janzamin
+	Guaranteed Non-Orthogonal Tensor Decomposition via Alternating Rank-$1$ Updates	2014	Animashree Anandkumar Rong Ge Majid Janzamin
+	Competing with the Empirical Risk Minimizer in a Single Pass	2014	Roy Frostig Rong Ge Sham M. Kakade Aaron Sidford
+	Tensor decompositions for learning latent variable models	2014	Animashree Anandkumar Rong Ge Daniel Hsu Sham M. Kakade Matus Telgarsky
+	More Algorithms for Provable Dictionary Learning	2014	Sanjeev Arora Aditya Bhaskara Rong Ge Tengyu Ma
+	Minimal Realization Problems for Hidden Markov Models	2014	Qingqing Huang Rong Ge Sham M. Kakade Munther A. Dahleh
+	A tensor approach to learning mixed membership community models	2014	Animashree Anandkumar Rong Ge Daniel Hsu Sham M. Kakade
+	Sample Complexity Analysis for Learning Overcomplete Latent Variable Models through Tensor Methods	2014	Animashree Anandkumar Rong Ge Majid Janzamin
+	Analyzing Tensor Power Method Dynamics in Overcomplete Regime	2014	Anima Anandkumar Rong Ge Majid Janzamin
+	Provable Bounds for Learning Some Deep Representations	2013	Sanjeev Arora Aditya Bhaskara Rong Ge Tengyu Ma
+ PDF Chat	Towards a Better Approximation for Sparsest Cut?	2013	Sanjeev Arora Rong Ge Ali Kemal Sinop
+	A Tensor Spectral Approach to Learning Mixed Membership Community Models	2013	Animashree Anandkumar Rong Ge Daniel Hsu Sham M. Kakade
+	Towards a better approximation for sparsest cut	2013	Sanjeev Arora Rong Ge Ali Kemal Sinop
+	A Tensor Spectral Approach to Learning Mixed Membership Community Models	2013	Anima Anandkumar Rong Ge Daniel Hsu Sham M. Kakade
+	A Tensor Approach to Learning Mixed Membership Community Models	2013	Anima Anandkumar Rong Ge Daniel Hsu Sham M. Kakade
+	Towards a better approximation for sparsest cut?	2013	Sanjeev Arora Rong Ge Ali Kemal Sinop
+	A Practical Algorithm for Topic Modeling with Provable Guarantees	2012	Sanjeev Arora Rong Ge Yoni Halpern David Mimno Ankur Moitra David Sontag Yichen Wu Michael Zhu
+ PDF Chat	Tensor Decompositions for Learning Latent Variable Models	2012	Anima Anandkumar Rong Ge Daniel Hsu Sham M. Kakade Matus Telgarsky
+ PDF Chat	Learning Topic Models -- Going beyond SVD	2012	Sanjeev Arora Rong Ge Ankur Moitra
+	Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders	2012	Sanjeev Arora Rong Ge Ankur Moitra Sushant Sachdeva
+	Learning Topic Models - Going beyond SVD	2012	Sanjeev Arora Rong Ge Ankur Moitra
+	A Practical Algorithm for Topic Modeling with Provable Guarantees	2012	Sanjeev Arora Rong Ge Yonatan Halpern David Mimno Ankur Moitra David Sontag Yichen Wu Michael Zhu
+	Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders	2012	Sanjeev Arora Rong Ge Ankur Moitra Sushant Sachdeva
+	Learning Topic Models - Going beyond SVD	2012	Sanjeev Arora Rong Ge Ankur Moitra
+	Tensor decompositions for learning latent variable models	2012	Anima Anandkumar Rong Ge Daniel Hsu Sham M. Kakade Matus Telgarsky
+	Finding Overlapping Communities in Social Networks: Toward a Rigorous Approach	2011	Sanjeev Arora Rong Ge Sushant Sachdeva Grant Schoenebeck
+	Evaluating online ad campaigns in a pipeline	2010	David Chan Rong Ge Ori Gershony Tim Hesterberg Diane Lambert

Common Coauthors

Coauthor	Papers Together
Sham M. Kakade	20
Sanjeev Arora	16
Majid Janzamin	12
Anima Anandkumar	11
Animashree Anandkumar	11
Daniel Hsu	8
Ankur Moitra	7
Debmalya Panigrahi	5
Abraham Frandsen	5
Qingqing Huang	5
Chi Jin	5
Praneeth Netrapalli	4
Matus Telgarsky	4
Tengyu Ma	3
Muthu Chidambaram	3
Munther A. Dahleh	3
Tengyu Ma	3
Ali Kemal Sinop	3
Xiang Wang	3
Michael I. Jordan	3
Sushant Sachdeva	3
Andrej Risteski	3
Keerti Anand	3
Yichen Wu	2
Aditya Bhaskara	2
Holden Lee	2
Haoyu Zhao	2
Zheng Miao	2
Amit Kumar	2
Furong Huang	2
Mo Zhou	2
David Sontag	2
Jason D. Lee	2
Arun Ganesh	2
Jiajia Li	2
David Mimno	2
Jean Kossaifi	2
Yuan Yang	2
Feng Luo	2
Abhishek Panigrahi	2
Yunwei Ren	2
Ilias Diakonikolas	2
Thomas Randall	2
Rahul Kidambi	2
Jon C. Calhoun	2
Pradip K. Srimani	2
James Zou	2
Roy Frostig	2
Yossi Azar	2
Chenwei Wu	2

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	A Method of Moments for Mixture Models and Hidden Markov Models	2012	Animashree Anandkumar Daniel Hsu Sham M. Kakade	15
+ PDF Chat	Learning mixtures of spherical gaussians	2013	Daniel Hsu Sham M. Kakade	15
+	Tensor decompositions for learning latent variable models	2014	Animashree Anandkumar Rong Ge Daniel Hsu Sham M. Kakade Matus Telgarsky	15
+	Tensor Decompositions and Applications	2009	Tamara G. Kolda Brett W. Bader	13
+	Two SVDs Suffice: Spectral decompositions for probabilistic topic modeling and latent Dirichlet allocation	2012	Animashree Anandkumar Dean P. Foster Daniel Hsu Sham M. Kakade Yi-Kai Liu	11
+ PDF Chat	User-Friendly Tail Bounds for Sums of Random Matrices	2011	Joel A. Tropp	10
+	Contrastive Learning Using Spectral Methods	2013	James Zou Daniel Hsu David C. Parkes Ryan P. Adams	10
+	Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics	1977	Joseph B. Kruskal	10
+	Rank-One Approximation to High Order Tensors	2001	Tong Zhang Gene H. Golub	10
+	A spectral algorithm for learning Hidden Markov Models	2012	Daniel Hsu Sham M. Kakade Tong Zhang	9
+	Fast Detection of Overlapping Communities via Online Tensor Methods	2013	Furong Huang U. N. Niranjan Mohammad Umar Hakeem Animashree Anandkumar	9
+ PDF Chat	Smoothed analysis of tensor decompositions	2014	Aditya Bhaskara Moses Charikar Ankur Moitra Aravindan Vijayaraghavan	9
+	Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multi-model factor analysis	1970	Richard A. Harshman	9
+ PDF Chat	Most Tensor Problems Are NP-Hard	2013	Christopher J. Hillar Lek‐Heng Lim	9
+	Shifted power method for computing tensor eigenpairs.	2010	Jackson Mayo Tamara G. Kolda	8
+	A Tensor Spectral Approach to Learning Mixed Membership Community Models	2013	Animashree Anandkumar Rong Ge Daniel Hsu Sham M. Kakade	8
+	Perturbation bounds in connection with singular value decomposition	1972	Per-Åke Wedin	7
+ PDF Chat	Singular Values and Eigenvalues of Tensors: A Variational Approach	2006	Lek‐Heng Lim	6
+ PDF Chat	Learning mixtures of separated nonspherical Gaussians	2005	Sanjeev Arora Ravi Kannan	6
+	Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition	1970	J. Douglas Carroll Jih-Jie Chang	6
+	Guaranteed Non-Orthogonal Tensor Decomposition via Alternating Rank-$1$ Updates	2014	Animashree Anandkumar Rong Ge Majid Janzamin	6
+	A Spectral Algorithm for Latent Dirichlet Allocation	2012	Animashree Anandkumar Dean P. Foster Daniel Hsu Sham M. Kakade Yi-Kai Liu	6
+ PDF Chat	Learning nonsingular phylogenies and hidden Markov models	2006	Elchanan Mossel Sébastien Roch	6
+	Sample Complexity Analysis for Learning Overcomplete Latent Variable Models through Tensor Methods	2014	Animashree Anandkumar Rong Ge Majid Janzamin	6
+	Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition	2015	Rong Ge Furong Huang Chi Jin Yuan Yang	5
+	Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm	1977	A. P. Dempster N. M. Laird Donald B. Rubin	5
+	A Decomposition for Three-Way Arrays	1993	Sue E. Leurgans R. Ross Robert Abel	5
+ PDF Chat	Learning nonsingular phylogenies and hidden Markov models	2005	Elchanan Mossel Sébastien Roch	5
+	Some methods for classification and analysis of multivariate observations	1967	James B. MacQueen	5
+	Eigenvalues of a real supersymmetric tensor	2005	Liqun Qi	5
+ PDF Chat	On exchangeable random variables and the statistics of large graphs and hypergraphs	2008	Tim Austin	5
+ PDF Chat	Computing a nonnegative matrix factorization -- provably	2012	Sanjeev Arora Rong Ge Ravindran Kannan Ankur Moitra	4
+	Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization	2013	Alekh Agarwal Animashree Anandkumar Prateek Jain Praneeth Netrapalli	4
+	Spectral partitioning of random graphs	2001	Frank McSherry	4
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	4
+	On the Best Rank-1 and Rank-(<i>R</i><sub>1</sub> ,<i>R</i><sub>2</sub> ,. . .,<i>R<sub>N</sub></i>) Approximation of Higher-Order Tensors	2000	Lieven De Lathauwer Bart De Moor Joos Vandewalle	4
+ PDF Chat	Low-rank matrix completion using alternating minimization	2013	Prateek Jain Praneeth Netrapalli Sujay Sanghavi	4
+	Online tensor methods for learning latent variable models	2015	Furong Huang U. N. Niranjan Mohammad Umar Hakeem Animashree Anandkumar	4
+	Polynomial Learning of Distribution Families	2010	Mikhail Belkin K. P. Sinha	4
+	Smoothed Analysis of Tensor Decompositions	2013	Aditya Bhaskara Moses Charikar Ankur Moitra Aravindan Vijayaraghavan	4
+ PDF Chat	Learning Mixtures of Gaussians in High Dimensions	2015	Rong Ge Qingqing Huang Sham M. Kakade	4
+	Decomposing Overcomplete 3rd Order Tensors using Sum-of-Squares Algorithms	2015	Rong Ge Tengyu Ma	4
+	The number of eigenvalues of a tensor	2011	Dustin Cartwright Bernd Sturmfels	4
+ PDF Chat	Dictionary Learning and Tensor Decomposition via the Sum-of-Squares Method	2015	Boaz Barak Jonathan A. Kelner David Steurer	4
+	A Method of Moments for Mixture Models and Hidden Markov Models	2012	Animashree Anandkumar Daniel Hsu Sham M. Kakade	4
+	Mixture Densities, Maximum Likelihood and the EM Algorithm	1984	Richard A. Redner Homer F. Walker	4
+	Sum-of-squares proofs and the quest toward optimal algorithms	2014	Boaz Barak David Steurer	4
+	On the uniqueness of multilinear decomposition ofN-way arrays	2000	Nicholas D. Sidiropoulos Rasmus Bro	4
+ PDF Chat	Settling the Polynomial Learnability of Mixtures of Gaussians	2010	Ankur Moitra Gregory Valiant	4
+	Learning mixtures of arbitrary gaussians	2001	Sanjeev Arora Ravi Kannan	4