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Lu, Yue M.

  1. Universality Laws for High-Dimensional Learning with Random Features
    2020/09/16 by Hong Hu, Yue M. Lu, Hu, Hong +1 · 18 citations
    Computer Science · Mathematics · #Stochastic Gradient Optimization Techniques #Markov Chains and Monte Carlo Methods #Random Matrices and Applications
  2. Asymptotic theory of in-context learning by linear attention
    2024/05/20 by Yue M. Lu, Lu, Yue M., Mary I. Letey +7 · 1 voice · 16 citations
    Computer Science · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
  3. Online Learning for Sparse PCA in High Dimensions: Exact Dynamics and Phase Transitions
    2016/09/07 by Wang, Chuang, Lu, Yue M. · 4 citations
    #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Computer and information sciences #FOS: Physical sciences #Information Theory (cs.IT)
  4. Scaling Limit: Exact and Tractable Analysis of Online Learning Algorithms with Applications to Regularized Regression and PCA
    2017/12/08 by Chuang Wang, Wang, Chuang, Jonathan C. Mattingly +3 · 5 citations
    Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Probability (math.PR) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  5. An Equivalence Principle for the Spectrum of Random Inner-Product Kernel Matrices with Polynomial Scalings
    2022/05/12 by Yue M. Lu, Horng‐Tzer Yau, Lu, Yue M. +1 · 6 citations
    Mathematics · Medicine · #Random Matrices and Applications #Advanced Algebra and Geometry #Advanced Neuroimaging Techniques and Applications
  6. Randomized Kaczmarz Algorithm for Inconsistent Linear Systems: An Exact MSE Analysis
    2015/02/01 by Wang, Chuang, Agaskar, Ameya, Lu, Yue M. · 3 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Numerical Analysis (math.NA) #Optimization and Control (math.OC)
  7. Spectral Universality of Regularized Linear Regression with Nearly Deterministic Sensing Matrices
    2022/08/04 by Rishabh Dudeja, Subhabrata Sen, Dudeja, Rishabh +3 · 5 citations
    Engineering · Mathematics · Computer Science · #Sparse and Compressive Sensing Techniques #Numerical methods in inverse problems #Distributed Sensor Networks and Detection Algorithms
  8. A Solvable High-Dimensional Model of GAN
    2018/05/22 by Chuang Wang, Wang, Chuang, Hong Hu +3 · 3 citations
    Computer Science · Engineering · Physics and Astronomy · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Computer and information sciences #FOS: Physical sciences #Generative Adversarial Networks and Image Synthesis #Information Theory (cs.IT) #Lattice Boltzmann Simulation Studies #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  9. A Precise Performance Analysis of Learning with Random Features
    2020/08/27 by Oussama Dhifallah, Yue M. Lu, Dhifallah, Oussama +1 · 6 citations
    Engineering · Computer Science · Mathematics · #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Statistical Methods and Inference
  10. The Scaling Limit of High-Dimensional Online Independent Component\n Analysis
    2017/10/15 by Chuang Wang, Yue M. Lu, Wang, Chuang +1 · 5 citations
    Computer Science · Engineering · #Blind Source Separation Techniques #Sparse and Compressive Sensing Techniques #Machine Learning and ELM
  11. Universality for the global spectrum of random inner-product kernel matrices in the polynomial regime
    2023/10/27 by Sofiia Dubova, Dubova, Sofiia, Yue M. Lu +5 · 5 citations
    Mathematics · #15B52 #60B20 #Advanced Algebra and Geometry #Advanced Combinatorial Mathematics #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Probability (math.PR) #Random Matrices and Applications
  12. Streaming PCA and Subspace Tracking: The Missing Data Case
    2018/06/12 by Balzano, Laura, Chi, Yuejie, Lu, Yue M. · 2 citations
    #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  13. On the Inherent Regularization Effects of Noise Injection During Training
    2021/02/15 by Oussama Dhifallah, Yue M. Lu, Dhifallah, Oussama +1 · 2 citations
    Computer Science · Engineering · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Information Theory (cs.IT) #Machine Learning (cs.LG) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  14. Householder Dice: A Matrix-Free Algorithm for Simulating Dynamics on\n Gaussian and Random Orthogonal Ensembles
    2021/01/18 by Yue M. Lu, Lu, Yue M. · 2 citations
    Mathematics · Physics and Astronomy · #Computation (stat.CO) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Information Theory (cs.IT) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Random Matrices and Applications #Statistics and Probability (physics.data-an) #Theoretical and Computational Physics
  15. Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime
    2024/03/13 by Hong Hu, Yue M. Lu, Hu, Hong +3 · 3 citations
    Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference #Statistics Theory (math.ST)
  16. A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities
    2024/10/24 by Yatin Dandi, Dandi, Yatin, Luca Pesce +9 · 4 citations
    Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Morphological variations and asymmetry #Neural Networks and Applications #Statistical Mechanics and Entropy #Statistics Theory (math.ST)
  17. Phase Transitions of Spectral Initialization for High-Dimensional\n Nonconvex Estimation
    2017/02/21 by Yue M. Lu, Lu, Yue M., Gen Li +1 · 1 citation
    Engineering · Mathematics · Physics and Astronomy · #Advanced X-ray Imaging Techniques #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (stat.ML) #Numerical methods in inverse problems #Sparse and Compressive Sensing Techniques
  18. Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime
    2022/05/13 by Hu, Hong, Lu, Yue M. · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  19. Precise Learning Curves and Higher-Order Scaling Limits for Dot Product Kernel Regression
    2022/05/30 by Xiao, Lechao, Hu, Hong, Misiakiewicz, Theodor +2 · 1 citation
    #68T07 #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  20. Dynamical mean-field analysis of adaptive Langevin diffusions: Propagation-of-chaos and convergence of the linear response
    2025/04/22 by Fan, Zhou, Jin Hwan Ko, Bruno Loureiro +6 · 2 citations
    Physics and Astronomy · #FOS: Mathematics #Model Reduction and Neural Networks #Probability (math.PR) #Statistics Theory (math.ST) #Theoretical and Computational Physics #stochastic dynamics and bifurcation