2018

Tal, Ezra; Gorodetsky, Alex; Karaman, Sertac

Continuous Tensor Train-Based Dynamic Programming for High-Dimensional Zero-Sum Differential Games Inproceedings Forthcoming

American Control Conference (ACC), Milwaukee, WI, Forthcoming.

Abstract | Links | BibTeX | Tags: Differential Games, Stochastic Optimal Control, Tensor decompositions

Geraci, Gianluca; Eldred, Michael S; Gorodetsky, Alex; Jakeman, John

Leveraging active subspaces for efficient multifidelity uncertainty quantification Inproceedings Forthcoming

ECCM-ECCFD, Glasgow, Scotland, UK, 2018 Forthcoming.

Abstract | Links | BibTeX | Tags: Active Subspace, Multifidelity Methods, Uncertainty Quantification

Gorodetsky, Alex; Karaman, Sertac; Marzouk, Youssef

High-Dimensional Stochastic Optimal Control using Continuous Tensor Decompositions Journal Article

International Journal of Robotics Research, 37 (2-3), pp. 340-377, 2018.

Abstract | Links | BibTeX | Tags: Dynamic Programming, Markov Decision Processes, Stochastic Optimal Control, Tensor decompositions

Kramer, Boris; Gorodetsky, Alex

System identification via CUR-factored Hankel approximation Journal Article

SIAM Journal on Scientific Computing, 40 (2), pp. A848–A866, 2018, ISSN: 1095-7197.

Abstract | Links | BibTeX | Tags: Low-rank approximation, model reduction, System Identification

Eldred, Michael S; Geraci, Gianluca; Gorodetsky, Alex; Jakeman, John

Multilevel-Multifidelity Approaches for Forward UQ in the DARPA SEQUOIA project Inproceedings

2018 AIAA Non-Deterministic Approaches Conference, AIAA SciTech Forum, Kissimmee, Florida, 2018.

Abstract | Links | BibTeX | Tags: Multifidelity Methods, Polynomial Approximation, Surrogate models, Tensor decompositions

Gorodetsky, Alex; Jakeman, John

Gradient-based Optimization for Regression in the Functional Tensor-Train Format Journal Article Forthcoming

Arxiv 1801.00885v2 (Accepted Journal of Computational Physics), Forthcoming.

Abstract | Links | BibTeX | Tags: Regression, Surrogate models, Tensor decompositions

2017

Gorodetsky, Alex; Karaman, Sertac; Marzouk, Youssef

Low-rank tensor integration for Gaussian filtering of continuous time nonlinear systems Inproceedings

2017 IEEE 56th Annual Conference on Decision and Control (CDC), pp. 2789-2794, Melbourne, VIC, Australia, 2017, ISBN: 978-1-5090-2873-3.

Abstract | Links | BibTeX | Tags: Dynamical Systems, Kalman Filtering, Tensor decompositions

Gorodetsky, Alex

Continuous low-rank tensor decompositions, with applications to stochastic optimal control and data assimilation PhD Thesis

Massachusetts Institute of Technology, 2017.

Abstract | Links | BibTeX | Tags: Dynamic Programming, Kalman Filtering, Stochastic Optimal Control, Surrogate models, Tensor decompositions

2016

Alora, John Irvin; Gorodetsky, Alex; Karaman, Sertac; Marzouk, Youssef; Lowry, Nathan

Automated synthesis of low-rank control systems from sc-LTL specifications using tensor-train decompositions Inproceedings

2016 IEEE 55th Conference on Decision and Control (CDC), pp. 1131-1138, Las Vegas, NV, USA, 2016, ISBN: 978-1-5090-1837-6.

Abstract | Links | BibTeX | Tags: Linear Temporal Logic, Stochastic Optimal Control, Tensor decompositions

Gorodetsky, Alex; Marzouk, Youssef

Mercer Kernels and Integrated Variance Experimental Design: Connections Between Gaussian Process Regression and Polynomial Approximation Journal Article

SIAM/ASA Journal of Uncertainty Quantification, 4 (1), pp. 796-828, 2016, ISSN: 2166-2525.

Abstract | Links | BibTeX | Tags: Experimental Design, Gaussian Process Regression, Polynomial Approximation

2015

Gorodetsky, Alex; Karaman, Sertac; Marzouk, Youssef

Efficient High-Dimensional Stochastic Optimal Motion Control using Tensor-Train Decomposition Inproceedings

Proceedings of Robotics: Science and Systems, Rome, Italy, 2015.

Abstract | Links | BibTeX | Tags: Dynamic Programming, Motion Planning, Stochastic Optimal Control, Tensor-train decomposition

2014

Gorodetsky, Alex; Marzouk, Youssef

Efficient Localization of Discontinuities in Complex Computational Simulations Journal Article

SIAM Journal on Scientific Computing, 36 (6), pp. A2584-A2610, 2014, ISSN: 1095-7197.

Abstract | Links | BibTeX | Tags: Active Learning, Support Vector Machines, Surrogate models