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  1. Courses
  2. 2017 SIAM Computational Sci...
  3. Inverse Problems Meet Big D...

Inverse Problems Meet Big Data - Part I of III

CSE17 - MS2-1: Fast Approximation of Kernel Matrices

Presentation: George Biros, University of Texas at Austin, USA, 21 min 2 sec

CSE17 - MS2-1: Fast Approximation of Kernel Matrices

Document: CSE17 - MS2-1: Fast Approximation of Kernel Matrices

CSE17 - MS2-2: Sketched Ridge Regression: Optimization and Statistical Perspectives

Presentation: Shusen Wang, University of California, Berkeley, USA, 14 min 8 sec

CSE17 - MS2-2: Sketched Ridge Regression: Optimization and Statistical Perspectives

Document: CSE17 - MS2-2: Sketched Ridge Regression: Optimization and Statistical Perspectives

CSE17 - MS2-3: Large Scale Fusion of Energy Resolved Compton Scatter and Attenuation-Based X-Ray Data for Materials Characterization

Presentation: Hamideh Rezaee, Tufts University, USA, 18 min 55 sec

CSE17 - MS2-3: Large Scale Fusion of Energy Resolved Compton Scatter and Attenuation-Based X-Ray Data for Materials Characterization

Document: CSE17 - MS2-3: Large Scale Fusion of Energy Resolved Compton Scatter and Attenuation-Based X-Ray Data for Materials Characterization

CSE17 - MS2-4: A Data Scalable Hessian/KKT Preconditioner for Large Scale Inverse Problems

Presentation: Nick Alger, University of Texas at Austin, USA, 24 min 0 sec

CSE17 - MS2-4: A Data Scalable Hessian/KKT Preconditioner for Large Scale Inverse Problems

Document: CSE17 - MS2-4: A Data Scalable Hessian/KKT Preconditioner for Large Scale Inverse Problems
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