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Becker, Stephen R Assistant Professor

Positions

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, 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 4720 - Open Topics in Applied Mathematics
    Primary Instructor - Fall 2018 / Spring 2019
    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.
  • APPM 5450 - Applied Analysis 2
    Primary Instructor - Spring 2018
    Continuation of APPM 5440. Department enforced prerequisite: APPM 5440.
  • APPM 5720 - Open Topics in Applied Mathematics
    Primary Instructor - Fall 2018 / Spring 2019
    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 6 total credit hours. Same as APPM 4720.
  • APPM 8500 - Statistics, Optimization and Machine Learning Seminar
    Primary Instructor - Spring 2018 / Fall 2018 / Spring 2019
    Research-level seminar that explores the mathematical foundations of machine learning, in particular how statistics and optimization give rise to well-founded and efficient algorithms.
  • CSCI 7000 - Current Topics in Computer Science
    Primary Instructor - Spring 2018 / Fall 2018
    Covers research topics of current interest in computer science that do not fall into a standard subarea. May be repeated up to 8 total credit hours.

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