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Avron, Haim

  1. Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
    2018/04/26 by Haim Avron, Michael Kapralov, Avron, Haim +9 · 8 citations
    Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Gaussian Processes and Bayesian Inference #Stochastic Gradient Optimization Techniques
  2. Faster Subset Selection for Matrices and Applications
    2011/12/30 by Haim Avron, Avron, Haim, Christos Boutsidis +1 · 4 citations
    Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Matrix Theory and Algorithms #Complexity and Algorithms in Graphs
  3. Stable Tensor Neural Networks for Rapid Deep Learning
    2018/11/15 by Elizabeth Newman, Lior Horesh, Newman, Elizabeth +5 · 5 citations
    Computer Science · Mathematics · Physics and Astronomy · #Computational Physics and Python Applications #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Tensor decomposition and applications
  4. Riemannian optimization with a preconditioning scheme on the generalized Stiefel manifold
    2019/02/05 by Boris Shustin, Shustin, Boris, Haim Avron +1 · 3 citations
    Computer Science · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Face and Expression Recognition #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Neural Networks and Applications #Numerical Analysis (math.NA) #Optimization and Control (math.OC)
  5. Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
    2014/12/29 by Haim Avron, Avron, Haim, Vikas Sindhwani +5 · 3 citations
    Mathematics · Medicine · Physics and Astronomy · #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mathematical Approximation and Integration #Medical Imaging Techniques and Applications #Nuclear Physics and Applications #Numerical Analysis (math.NA)
  6. Sharper Bounds for Regularized Data Fitting
    2016/11/10 by Haim Avron, Kenneth L. Clarkson, Avron, Haim +3 · 2 citations
    Computer Science · Engineering · #Complexity and Algorithms in Graphs #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  7. Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization
    2012/06/27 by Haim Avron, Avron, Haim, Satyen Kale +5 · 2 citations
    Computer Science · Engineering · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  8. Semi-Infinite Linear Regression and Its Applications
    2021/04/12 by Shustin, Paz Fink, Avron, Haim · 2 citations
    #FOS: Mathematics #Numerical Analysis (math.NA)
  9. Scaling Neural Tangent Kernels via Sketching and Random Features
    2021/06/15 by Zandieh, Amir, Han, Insu, Avron, Haim +3 · 2 citations
    #Computer Vision and Pattern Recognition (cs.CV) #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  10. Stochastic Chebyshev Gradient Descent for Spectral Optimization
    2018/02/18 by In‐Su Han, Haim Avron, Han, Insu +3 · 2 citations
    Computer Science · Engineering · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Machine Learning and ELM
  11. Gauss-Legendre Features for Gaussian Process Regression
    2021/01/04 by Paz Fink Shustin, Haim Avron, Shustin, Paz Fink +1 · 2 citations
    Computer Science · #Gaussian Processes and Bayesian Inference #Advanced Multi-Objective Optimization Algorithms #Machine Learning and Data Classification
  12. PCENet: High Dimensional Surrogate Modeling for Learning Uncertainty
    2022/02/10 by Paz Fink Shustin, Shustin, Paz Fink, Shashanka Ubaru +9 · 2 citations
    Computer Science · Decision Sciences · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Probabilistic and Robust Engineering Design
  13. Effective Stiffness: Generalizing Effective Resistance Sampling to Finite Element Matrices
    2011/10/20 by Haim Avron, Avron, Haim, Sivan Toledo +1 · 1 citation
    Computer Science · Decision Sciences · #Complexity and Algorithms in Graphs #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Matrix Theory and Algorithms #Numerical Analysis (math.NA) #Probabilistic and Robust Engineering Design
  14. A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms
    2018/12/20 by Avron, Haim, Kapralov, Michael, Musco, Cameron +3 · 1 citation
    #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Signal Processing (eess.SP) #electronic engineering #information engineering
  15. Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix
    2019/05/28 by Han, Insu, Avron, Haim, Shin, Jinwoo · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  16. Low-Rank Updates of Matrix Square Roots
    2022/01/31 by Shumeli, Shany, Drineas, Petros, Avron, Haim · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA)
  17. Near Optimal Reconstruction of Spherical Harmonic Expansions
    2022/02/25 by Zandieh, Amir, Han, Insu, Avron, Haim · 1 citation
    #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Signal Processing (eess.SP) #electronic engineering #information engineering
  18. Manifold Free Riemannian Optimization
    2022/09/07 by Shustin, Boris, Avron, Haim, Sober, Barak · 1 citation
    #Computational Geometry (cs.CG) #Differential Geometry (math.DG) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Numerical Analysis (math.NA) #Optimization and Control (math.OC)
  19. Faster Randomized Interior Point Methods for Tall/Wide Linear Programs
    2022/09/19 by Agniva Chowdhury, Gregory Dexter, Chowdhury, Agniva +7 · 1 citation
    Computer Science · Mathematics · #Advanced Optimization Algorithms Research #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Matrix Theory and Algorithms #Tensor decomposition and applications
  20. Hierarchically Compositional Kernels for Scalable Nonparametric Learning
    2016/08/02 by Jie Chen, Haim Avron, Chen, Jie +3 · 2 citations
    Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Face and Expression Recognition #Machine Learning and ELM
  21. Hutchinson's Estimator is Bad at Kronecker-Trace-Estimation
    2023/09/10 by Raphael A. Meyer, Haim Avron, Meyer, Raphael A. +1 · 1 citation
    Engineering · Computer Science · Mathematics · #Sparse and Compressive Sensing Techniques #Blind Source Separation Techniques #Random Matrices and Applications
  22. Faster Kernel Ridge Regression Using Sketching and Preconditioning
    2016/11/10 by Haim Avron, Kenneth L. Clarkson, Avron, Haim +3 · 2 citations
    Computer Science · Engineering · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques