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.
Robust Partially-Compressed Least-Squares.
Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence.
1742-1748.
2017
METRIC LEARNING WITH RANK AND SPARSITY CONSTRAINTS.
Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing / sponsored by the Institute of Electrical and Electronics Engineers Signal Processing Society. ICASSP (Conference).
2014
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.
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 / 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 6 total credit hours. Same as APPM 4720.
APPM 6950 - Master's Thesis
Primary Instructor
-
Fall 2021 / Summer 2022 / Fall 2023 / Spring 2024 / Fall 2024
May be repeated up to 6 total credit hours.
APPM 7400 - Topics in Applied Mathematics
Primary Instructor
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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 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 engineering. Content varies by instructor and semester. May be repeated up to 9 total credit hours.
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 18 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 prerequisite: 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. Recommended prerequisite: previous coursework equivalent to STAT 4520 or MATH 4520 or STAT 5520 or MATH 5520; minimum grade of C- for all. Same as STAT 4540 and MATH 4540 and MATH 5540.
