vix.ing · top · new · best · stats · spec

Rong Ge

  1. Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition
    2015/03/06 by Rong Ge, Furong Huang, Ge, Rong +5 · 123 citations
    Mathematics · Engineering · Computer Science · #Tensor decomposition and applications #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  2. Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
    2018/01/15 by Maryam Fazel, Rong Ge, Fazel, Maryam +5 · 50 citations
    Computer Science · Engineering · Physics and Astronomy · #Adaptive Dynamic Programming Control #Advanced Control Systems Optimization #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  3. How to Escape Saddle Points Efficiently
    2017/03/02 by Chi Jin, Jin, Chi, Rong Ge +7 · 36 citations
    Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  4. Stronger generalization bounds for deep nets via a compression approach
    2018/02/14 by Sanjeev Arora, Rong Ge, Arora, Sanjeev +5 · 36 citations
    Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Stochastic Gradient Optimization Techniques
  5. No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified\n Geometric Analysis
    2017/04/03 by Rong Ge, Ge, Rong, Chi Jin +3 · 32 citations
    Engineering · Mathematics · Computer Science · #Sparse and Compressive Sensing Techniques #Advanced Optimization Algorithms Research #Stochastic Gradient Optimization Techniques
  6. Learning Topic Models - Going beyond SVD
    2012/04/09 by Sanjeev Arora, Arora, Sanjeev, Rong Ge +3 · 18 citations
    Computer Science · #Topic Modeling #Text and Document Classification Technologies #Advanced Text Analysis Techniques
  7. A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm
    2019/02/11 by Chi Jin, Praneeth Netrapalli, Jin, Chi +7 · 13 citations
    Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mathematical Approximation and Integration #Point processes and geometric inequalities #Probability (math.PR) #Random Matrices and Applications
  8. A Practical Algorithm for Topic Modeling with Provable Guarantees
    2012/12/19 by Sanjeev Arora, Arora, Sanjeev, Rong Ge +13 · 9 citations
    Computer Science · #Topic Modeling #Advanced Graph Neural Networks #Text and Document Classification Technologies
  9. Learning One-hidden-layer Neural Networks with Landscape Design
    2017/11/01 by Rong Ge, Ge, Rong, Jason D. Lee +3 · 24 citations
    Computer Science · #Stochastic Gradient Optimization Techniques #Machine Learning and Algorithms #Machine Learning and ELM
  10. Computing a Nonnegative Matrix Factorization -- Provably
    2011/11/03 by Sanjeev Arora, Rong Ge, Arora, Sanjeev +5 · 9 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · #DNA and Biological Computing #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Quantum Computing Algorithms and Architecture #graph theory and CDMA systems
  11. ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods
    2024/06/23 by Roy Xie, Junlin Wang, Xie, Roy +13 · 18 citations
    Decision Sciences · #Computation and Language (cs.CL) #Data Quality and Management #FOS: Computer and information sciences #Machine Learning (cs.LG)
  12. Un-regularizing: approximate proximal point and faster stochastic\n algorithms for empirical risk minimization
    2015/06/24 by Roy Frostig, Rong Ge, Frostig, Roy +5 · 8 citations
    Computer Science · Decision Sciences · Engineering · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Risk and Portfolio Optimization #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  13. The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning\n Rate Procedure For Least Squares
    2019/04/29 by Rong Ge, Sham M. Kakade, Ge, Rong +5 · 6 citations
    Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  14. High-Dimensional Robust Mean Estimation in Nearly-Linear Time
    2018/11/23 by Yu Cheng, Ilias Diakonikolas, Cheng, Yu +3 · 5 citations
    Computer Science · Mathematics · #Adversarial Robustness in Machine Learning #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Statistical Methods and Inference #Statistics Theory (math.ST)
  15. A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network
    2021/02/04 by Mo Zhou, Zhou, Mo, Rong Ge +3 · 6 citations
    Computer Science · #Neural Networks and Applications #Advanced Neural Network Applications #Stochastic Gradient Optimization Techniques
  16. Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks
    2020/10/08 by Yikai Wu, Wu, Yikai, Xingyu Zhu +7 · 5 citations
    Computer Science · Engineering · #FOS: Computer and information sciences #Face and Expression Recognition #I.2.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  17. Finding Overlapping Communities in Social Networks: Toward a Rigorous Approach
    2011/12/08 by Sanjeev Arora, Arora, Sanjeev, Rong Ge +5 · 3 citations
    Physics and Astronomy · Computer Science · #Complex Network Analysis Techniques #Opinion Dynamics and Social Influence #Peer-to-Peer Network Technologies
  18. Homotopy Analysis for Tensor PCA
    2016/10/28 by Anima Anandkumar, Yuan Deng, Anandkumar, Anima +5 · 3 citations
    Engineering · Mathematics · #Advanced Optimization Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Tensor decomposition and applications
  19. Customizing ML Predictions for Online Algorithms
    2022/05/18 by Keerti Anand, Rong Ge, Anand, Keerti +3 · 3 citations
    Computer Science · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification #Optimization and Search Problems
  20. Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian\n Mixtures and Autoencoders
    2012/06/22 by Sanjeev Arora, Rong Ge, Arora, Sanjeev +5 · 2 citations
    Computer Science · Engineering · #Blind Source Separation Techniques #Machine Learning and Algorithms #Sparse and Compressive Sensing Techniques
  21. A Regression Approach to Learning-Augmented Online Algorithms
    2022/05/18 by Keerti Anand, Anand, Keerti, Rong Ge +5 · 2 citations
    Computer Science · Decision Sciences · #Online Learning and Analytics #Advanced Bandit Algorithms Research #Optimization and Search Problems
  22. Understanding Edge-of-Stability Training Dynamics with a Minimalist Example
    2022/10/07 by Xingyu Zhu, Zixuan Wang, Zhu, Xingyu +7 · 2 citations
    Computer Science · Engineering · Physics and Astronomy · #Advanced Memory and Neural Computing #FOS: Computer and information sciences #FOS: Mathematics #I.2.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications #Optimization and Control (math.OC)
  23. Understanding Deflation Process in Over-parametrized Tensor Decomposition
    2021/06/11 by Rong Ge, Ge, Rong, Yunwei Ren +5 · 1 citation
    Engineering · Mathematics · Medicine · #Advanced Neuroimaging Techniques and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Tensor decomposition and applications
  24. Mildly Overparametrized Neural Nets can Memorize Training Data Efficiently
    2019/09/26 by Rong Ge, Ge, Rong, Runzhe Wang +3 · 2 citations
    Computer Science · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Stochastic Gradient Optimization Techniques
  25. Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis
    2016/04/13 by Rong Ge, Ge, Rong, Chi Jin +7 · 1 citation
    Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Topological and Geometric Data Analysis
  26. On the Limitations of Temperature Scaling for Distributions with Overlaps
    2023/06/01 by Muthu Chidambaram, Chidambaram, Muthu, Rong Ge +1 · 1 citation
    Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
  27. How Does Gradient Descent Learn Features -- A Local Analysis for Regularized Two-Layer Neural Networks
    2024/06/03 by Mo Zhou, Rong Ge, Zhou, Mo +1 · 1 citation
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
  28. Reassessing How to Compare and Improve the Calibration of Machine Learning Models
    2024/06/06 by Muthu Chidambaram, Rong Ge, Chidambaram, Muthu +1 · 1 citation
    Computer Science · Engineering · #Advanced Data Processing Techniques #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Statistics Theory (math.ST)
  29. Competing with the Empirical Risk Minimizer in a Single Pass
    2014/12/20 by Roy Frostig, Rong Ge, Frostig, Roy +5 · 1 citation
    Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  30. MEDA: Measurement-Efficient Disorder-Aware Majorana Zero Mode Detection in Realistic Devices
    2026/07/28 by Nathan Jones, Binayyak Roy, Valentine Mohaugen +4
    Computer Science · Physics and Astronomy · #cs.ET #quant-ph