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papers

Publications (46)

cs.LG2018

High-Dimensional Robust Mean Estimation in Nearly-Linear Time

Yu Cheng, Ilias Diakonikolas, Rong Ge

cs.LG2015

Analyzing Tensor Power Method Dynamics in Overcomplete Regime

Anima Anandkumar, Rong Ge, Majid Janzamin

cs.LG2017

Learning One-hidden-layer Neural Networks with Landscape Design

Rong Ge, Jason D. Lee, Tengyu Ma

cs.LG2017

No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis

Rong Ge, Chi Jin, Yi Zheng

math.PR2019

A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Chi Jin, Praneeth Netrapalli, Rong Ge +2

cs.LG2012

A Practical Algorithm for Topic Modeling with Provable Guarantees

Sanjeev Arora, Rong Ge, Yoni Halpern +5

cs.LG2013

Provable Bounds for Learning Some Deep Representations

Sanjeev Arora, Aditya Bhaskara, Rong Ge +1

cs.DS2011

Computing a Nonnegative Matrix Factorization -- Provably

Sanjeev Arora, Rong Ge, Ravi Kannan +1

stat.ML2017

Homotopy Analysis for Tensor PCA

Anima Anandkumar, Yuan Deng, Rong Ge +1

cs.LG2015

Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition

Rong Ge, Furong Huang, Chi Jin +1

cs.LG2012

Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders

Sanjeev Arora, Rong Ge, Ankur Moitra +1

cs.LG2015

Minimal Realization Problems for Hidden Markov Models

Qingqing Huang, Rong Ge, Sham Kakade +1

cs.LG2012

Learning Topic Models - Going beyond SVD

Sanjeev Arora, Rong Ge, Ankur Moitra

cs.LG2016

Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis

Rong Ge, Chi Jin, Sham M. Kakade +2

cs.LG2016

Efficient approaches for escaping higher order saddle points in non-convex optimization

Anima Anandkumar, Rong Ge

cs.LG2015

Intersecting Faces: Non-negative Matrix Factorization With New Guarantees

Rong Ge, James Zou

cs.LG2017

Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo

Rong Ge, Holden Lee, Andrej Risteski

cs.LG2019

Learning Two-layer Neural Networks with Symmetric Inputs

Rong Ge, Rohith Kuditipudi, Zhize Li +1

cs.LG2017

On the Optimization Landscape of Tensor Decompositions

Rong Ge, Tengyu Ma

cs.LG2017

Generalization and Equilibrium in Generative Adversarial Nets (GANs)

Sanjeev Arora, Rong Ge, Yingyu Liang +2

cs.PF2016

DynIMS: A Dynamic Memory Controller for In-memory Storage on HPC Systems

Pengfei Xuan, Feng Luo, Rong Ge +1

cs.LG2015

Rich Component Analysis

Rong Ge, James Zou

cs.LG2015

Simple, Efficient, and Neural Algorithms for Sparse Coding

Sanjeev Arora, Rong Ge, Tengyu Ma +1

cs.LG2018

On the Local Minima of the Empirical Risk

Chi Jin, Lydia T. Liu, Rong Ge +1

cs.LG2018

Matrix Completion has No Spurious Local Minimum

Rong Ge, Jason D. Lee, Tengyu Ma

cs.DS2017

Online Service with Delay

Yossi Azar, Arun Ganesh, Rong Ge +1

cs.SI2011

Finding Overlapping Communities in Social Networks: Toward a Rigorous Approach

Sanjeev Arora, Rong Ge, Sushant Sachdeva +1

cs.LG2018

Non-Convex Matrix Completion Against a Semi-Random Adversary

Yu Cheng, Rong Ge

cs.LG2019

Understanding Composition of Word Embeddings via Tensor Decomposition

Abraham Frandsen, Rong Ge

cs.DS2015

Decomposing Overcomplete 3rd Order Tensors using Sum-of-Squares Algorithms

Rong Ge, Tengyu Ma

cs.LG2016

Provable Algorithms for Inference in Topic Models

Sanjeev Arora, Rong Ge, Frederic Koehler +2

stat.ML2015

Competing with the Empirical Risk Minimizer in a Single Pass

Roy Frostig, Rong Ge, Sham M. Kakade +1

cs.LG2013

A Tensor Approach to Learning Mixed Membership Community Models

Anima Anandkumar, Rong Ge, Daniel Hsu +1

cs.LG2019

Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator

Maryam Fazel, Rong Ge, Sham M. Kakade +1

cs.LG2019

Faster Algorithms for High-Dimensional Robust Covariance Estimation

Yu Cheng, Ilias Diakonikolas, Rong Ge +1

cs.LG2018

Stronger generalization bounds for deep nets via a compression approach

Sanjeev Arora, Rong Ge, Behnam Neyshabur +1

cs.LG2014

Sample Complexity Analysis for Learning Overcomplete Latent Variable Models through Tensor Methods

Animashree Anandkumar, Rong Ge, Majid Janzamin

cs.LG2019

Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization

Rong Ge, Zhize Li, Weiyao Wang +1

stat.ML2015

Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization

Roy Frostig, Rong Ge, Sham M. Kakade +1

cs.DS2014

More Algorithms for Provable Dictionary Learning

Sanjeev Arora, Aditya Bhaskara, Rong Ge +1

cs.LG2016

Provable learning of Noisy-or Networks

Sanjeev Arora, Rong Ge, Tengyu Ma +1

cs.DS2014

New Algorithms for Learning Incoherent and Overcomplete Dictionaries

Sanjeev Arora, Rong Ge, Ankur Moitra

cs.LG2015

Learning Mixtures of Gaussians in High Dimensions

Rong Ge, Qingqing Huang, Sham M. Kakade

cs.LG2017

How to Escape Saddle Points Efficiently

Chi Jin, Rong Ge, Praneeth Netrapalli +2

cs.DC2015

Big Data Analytics on Traditional HPC Infrastructure Using Two-Level Storage

Pengfei Xuan, Jeffrey Denton, Rong Ge +2

cs.DS2013

Towards a better approximation for sparsest cut?

Sanjeev Arora, Rong Ge, Ali Kemal Sinop