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Becker, Stephen R

Associate Professor

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Research Areas research areas

Research

research overview

  • Dr. Becker's group is centered around optimization, both creating algorithms to solve optimization problems and applying optimization to real-world problems. Most applications revolve around signal processing and statistical estimation, especially compressed sensing, matrix completion and various machine learning techniques.

keywords

  • continuous optimization, derivative free optimization, signal processing, compressed sensing, inverse problems, machine learning, high-dimensional statistical estimation, convex analysis, numerical analysis

Publications

selected publications

Teaching

courses taught

  • APPM 2360 - Introduction to Differential Equations with Linear Algebra
    Primary Instructor - Fall 2018
    Introduces ordinary differential equations, systems of linear equations, matrices, determinants, vector spaces, linear transformations, and systems of linear differential equations. Credit not granted for this course and both MATH 2130 and MATH 3430.
  • APPM 4440 - Undergraduate Applied Analysis 1
    Primary Instructor - Fall 2023
    Provides a rigorous treatment of topics covered in Calculus 1 and 2. Topics include convergent sequences; continuous functions; differentiable functions; Darboux sums, Riemann sums, and integration; Taylor and power series and sequences of functions.
  • APPM 4490 - Theory of Machine Learning
    Primary Instructor - Spring 2022 / Spring 2024
    Presents the underlying theory behind machine learning in proofs-based format. Answers fundamental questions about what learning means and what can be learned via formal models of statistical learning theory. Analyzes some important classes of machine learning methods. Specific topics may include the PAC framework, VC-dimension and Rademacher complexity. Recommended prerequisite: CSCI 5622 (minimum grade C-).
  • APPM 4650 - Intermediate Numerical Analysis 1
    Primary Instructor - Fall 2020
    Focuses on numerical solution of nonlinear equations, interpolation, methods in numerical integration, numerical solution of linear systems, and matrix eigenvalue problems. Stresses significant computer applications and software. Department enforced prerequisite: knowledge of a programming language. Same as MATH 4650.
  • APPM 4720 - Open Topics in Applied Mathematics
    Primary Instructor - Fall 2018 / Spring 2019 / Fall 2024
    Provides a vehicle for the development and presentation of new topics that may be incorporated into the core courses in applied mathematics. Department enforced prerequisite: variable, depending on the topic, see instructor. May be repeated up to 15 total credit hours. Same as APPM 5720.
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