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Sen Na

Sen Na

PhD (2016-2021)

University of Chicago Department of Statistics

Sen Na was a PhD student in the Department of Statistics at The University of Chicago. Prior to graduate school, he obtained BS in mathematics at Nanjing University, China. His research interests lie in nonlinear and nonconvex optimization, dynamic programming, high-dimensional statistics and their interface.

Personal webpage

Interests
  • Nonlinear Optimization
  • Dynamic Programming
  • High-Dimensional Statistics
Education
  • PhD in Statistics, 2021

    University of Chicago

  • BS in Mathematics, 2016

    Nanjing University

Latest

  • Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems
  • An adaptive stochastic sequential quadratic programming with differentiable exact augmented lagrangians
  • Inequality Constrained Stochastic Nonlinear Optimization via Active-Set Sequential Quadratic Programming
  • A Fast Temporal Decomposition Procedure for Long-horizon Nonlinear Dynamic Programming
  • Estimating differential latent variable graphical models with applications to brain connectivity
  • High-dimensional Index Volatility Models via Stein's Identity
  • Convergence Analysis of Accelerated Stochastic Gradient Descent under the Growth Condition
  • Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
  • High-dimensional Varying Index Coefficient Models via Stein's Identity
  • Scalable Peaceman-Rachford Splitting Method with Proximal Terms

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