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Becker, Stephen R

Associate 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, 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
    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 5440 - Applied Analysis 1
    Primary Instructor - Fall 2019
    Discusses the elements of basic real and complex analysis, Banach spaces, Lp spaces and many relevant inequalities. Includes applications of existence and uniqueness of solutions to various types of ordinary differential equations, partial differential equations, and integral equations. Department enforced prerequisites: APPM 4440 and APPM 4450.
  • APPM 5450 - Applied Analysis 2
    Primary Instructor - Spring 2018 / Spring 2023
    Continuation of APPM 5440. Department enforced prerequisite: APPM 5440.
  • APPM 5490 - 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 prerequisites: APPM 4440 and CSCI 5622.
  • APPM 5630 - Advanced Convex Optimization
    Primary Instructor - Spring 2021 / Spring 2023
    Investigates landmark convex optimization algorithms and their complexity results. Studies theoretical foundations while also surveying current practical state-of-the-art methods. Topics may include Fenchel-Rockafellar duality, KKT conditions, proximal methods, and Nesterov acceleration. Recommended prerequisites: APPM 4440 or equivalent, and familiarity with linear programming.
  • APPM 5650 - Randomized Algorithms
    Primary Instructor - Fall 2021
    Investigates modern randomized methods that are used in scientific and numerical computing, in particular randomized matrix approximation methods. Other topics may include stochastic gradient methods and variance reduced versions, compressed sensing, and locality sensitive hashing. Same as STAT 5650. Recommended prerequisite: APPM 4440 or equivalent.
  • 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 6950 - Master's Thesis
    Primary Instructor - Fall 2021 / Summer 2022 / Fall 2023 / Spring 2024
    May be repeated up to 6 total credit hours.
  • APPM 7400 - Topics in Applied Mathematics
    Primary Instructor - Spring 2020
    Provides a vehicle for the development and presentation of new topics with the potential of being incorporated into the core courses in applied mathematics. May be repeated up to 6 total credit hours.
  • APPM 8000 - Colloquium in Applied Mathematics
    Primary Instructor - Fall 2023
    Introduces graduate students to the major research foci of the Department of Applied Mathematics.
  • APPM 8500 - Statistics, Optimization and Machine Learning Seminar
    Primary Instructor - Spring 2018 / Fall 2018 / Spring 2019 / Fall 2019 / Spring 2020 / Fall 2021 / Spring 2022
    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.
  • COEN 1830 - Special Topics
    Primary Instructor - Fall 2023
    Explores topics of interest in transitioning to the College of Engineering and succeeding in STEM majors.
  • CSCI 4830 - Special Topics in Computer Science
    Primary Instructor - Fall 2021
    Covers topics of interest in computer science at the senior undergraduate level. Content varies from semester to semester. Only 9 credit hours from CSCI 4830 and/or CSCI 4831 can count toward Computer Science BS or BA.
  • CSCI 7000 - Current Topics in Computer Science
    Primary Instructor - Fall 2018 / Fall 2019 / Fall 2021
    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.
  • MATH 4540 - Introduction to Time Series
    Primary Instructor - Spring 2022
    Studies basic properties, trend-based models, seasonal models, modeling and forecasting with ARIMA models, spectral analysis and frequency filtration. Same as MATH 5540 and STAT 4540 and STAT 5540.
  • MATH 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 restriction: knowledge of a programming language. Same as APPM 4650.
  • MATH 5540 - Introduction to Time Series
    Primary Instructor - Spring 2022
    Studies basic properties, trend-based models, seasonal models, modeling and forecasting with ARIMA models, spectral analysis and frequency filtration. Department enforced prerequisite: MATH 4520 or MATH 5520 or APPM 4520 or APPM 5520. Same as MATH 4540 and STAT 4540 and STAT 5540.
  • STAT 4540 - Introduction to Time Series
    Primary Instructor - Spring 2022
    Studies basic properties, trend-based models, seasonal models modeling and forecasting with ARIMA models, spectral analysis and frequency filtration. Same as STAT 5540 and MATH 4540 and MATH 5540.
  • STAT 5540 - Introduction to Time Series
    Primary Instructor - Spring 2022
    Studies basic properties, trend-based models, seasonal models modeling and forecasting with ARIMA models, spectral analysis and frequency filtration. Department enforced prerequisite: APPM 5520 or MATH 5520. Same as STAT 4540 and MATH 4540 and MATH 5540.

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