Aleksandr Y. Aravkin

Orcid: 0000-0002-1875-1801

According to our database1, Aleksandr Y. Aravkin authored at least 93 papers between 2010 and 2025.

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Bibliography

2025
Deep networks for system identification: A survey.
Autom., 2025

2024
A Levenberg-Marquardt Method for Nonsmooth Regularized Least Squares.
SIAM J. Sci. Comput., 2024

A Relaxation Approach to Feature Selection for Linear Mixed Effects Models.
J. Comput. Graph. Stat., 2024

Uncertainty Quantification under Noisy Constraints, with Applications to Raking.
CoRR, 2024

Learning Nonlinear Dynamics Using Kalman Smoothing.
IEEE Access, 2024

Ensemble Principal Component Analysis.
IEEE Access, 2024

2023
pysr3: A Python Package for Sparse Relaxed Regularized Regression.
J. Open Source Softw., June, 2023

2022
A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimization.
SIAM J. Optim., 2022

Robust and Scalable Methods for the Dynamic Mode Decomposition.
SIAM J. Appl. Dyn. Syst., 2022

Robust trimmed k-means.
Pattern Recognit. Lett., 2022

A Nonconvex Optimization Approach to IMRT Planning with Dose-Volume Constraints.
INFORMS J. Comput., 2022

Spatiotemporal k-means.
CoRR, 2022

2021
On the Global Minimizers of Real Robust Phase Retrieval With Sparse Noise.
IEEE Trans. Inf. Theory, 2021

Efficient Robust Parameter Identification in Generalized Kalman Smoothing Models.
IEEE Trans. Autom. Control., 2021

$\ell _{1}$-Norm Minimization With Regula Falsi Type Root Finding Methods.
IEEE Signal Process. Lett., 2021

Variable Projection for NonSmooth Problems.
SIAM J. Sci. Comput., 2021

Time-Varying Autoregression with Low-Rank Tensors.
SIAM J. Appl. Dyn. Syst., 2021

Estimating Shape Parameters of Piecewise Linear-Quadratic Problems.
Open J. Math. Optim., 2021

Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks.
Neural Comput., 2021

Trimmed Constrained Mixed Effects Models: Formulations and Algorithms.
J. Comput. Graph. Stat., 2021

Theoretical Advances in Current Estimation and Navigation from a Glider-Based Acoustic Doppler Current Profiler (ADCP).
CoRR, 2021

A feasibility study of a hyperparameter tuning approach to automated inverse planning in radiotherapy.
CoRR, 2021

Analysis of Truncated Orthogonal Iteration for Sparse Eigenvector Problems.
CoRR, 2021

Stable and robust LQR design via scenario approach.
Autom., 2021

2020
Sparse Principal Component Analysis via Variable Projection.
SIAM J. Appl. Math., 2020

Trimmed Statistical Estimation via Variance Reduction.
Math. Oper. Res., 2020

Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning.
CoRR, 2020

Physics-informed machine learning for sensor fault detection with flight test data.
CoRR, 2020

Offline state estimation for hybrid systems via nonsmooth variable projection.
Autom., 2020

Sparse mean-reverting portfolios via penalized likelihood optimization.
Autom., 2020

A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data.
IEEE Access, 2020

2019
Basis Pursuit Denoise With Nonsmooth Constraints.
IEEE Trans. Signal Process., 2019

Adapting Regularized Low-Rank Models for Parallel Architectures.
SIAM J. Sci. Comput., 2019

Level-set methods for convex optimization.
Math. Program., 2019

Boosting as a kernel-based method.
Mach. Learn., 2019

Fast robust methods for singular state-space models.
Autom., 2019

A Unified Framework for Sparse Relaxed Regularized Regression: SR3.
IEEE Access, 2019

Robust Singular Smoothers for Tracking Using Low-Fidelity Data.
Proceedings of the Robotics: Science and Systems XV, 2019

Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

A Relaxed Optimization Approach for Cardinality-Constrained Portfolios.
Proceedings of the 17th European Control Conference, 2019

2018
Efficient Quadratic Penalization Through the Partial Minimization Technique.
IEEE Trans. Autom. Control., 2018

Generalized System Identification with Stable Spline Kernels.
SIAM J. Sci. Comput., 2018

Foundations of Gauge and Perspective Duality.
SIAM J. Optim., 2018

Total Variation Regularization Strategies in Full-Waveform Inversion.
SIAM J. Imaging Sci., 2018

Sparse Relaxed Regularized Regression: SR3.
CoRR, 2018

Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM.
CoRR, 2018

Sparse Principal Component Analysis via Variable Projection.
CoRR, 2018

Mean Reverting Portfolios via Penalized OU-Likelihood Estimation.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017
Beating Level-Set Methods for 5-D Seismic Data Interpolation: A Primal-Dual Alternating Approach.
IEEE Trans. Computational Imaging, 2017

Generalized Kalman smoothing: Modeling and algorithms.
Autom., 2017

Learning Robust Representations for Computer Vision.
Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

Distributed Bundle Adjustment.
Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

2016
Analytics for understanding customer behavior in the energy and utility industry.
IBM J. Res. Dev., 2016

A SMART Stochastic Algorithm for Nonconvex Optimization with Applications to Robust Machine Learning.
CoRR, 2016

Dual Smoothing and Level Set Techniques for Variational Matrix Decomposition.
CoRR, 2016

Robust EM kernel-based methods for linear system identification.
Autom., 2016

A stable spline convex approach to hybrid systems identification.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Dynamic matrix factorization with social influence.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Beyond L2-loss functions for learning sparse models.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015
The Connection Between Bayesian Estimation of a Gaussian Random Field and RKHS.
IEEE Trans. Neural Networks Learn. Syst., 2015

Source estimation for wave equations with uncertain parameters.
Proceedings of the 14th European Control Conference, 2015

Adaptive as-natural-as-possible image stitching.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Outlier robust kernel-based system identification using ℓ1-Laplace techniques.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2014
Fast Methods for Denoising Matrix Completion Formulations, with Applications to Robust Seismic Data Interpolation.
SIAM J. Sci. Comput., 2014

Robust and Trend-Following Student's t Kalman Smoothers.
SIAM J. Control. Optim., 2014

Convex vs non-convex estimators for regression and sparse estimation: the mean squared error properties of ARD and GLasso.
J. Mach. Learn. Res., 2014

Sparse Quantile Huber Regression for Efficient and Robust Estimation.
CoRR, 2014

Semistochastic Quadratic Bound Methods for Convex and Nonconvex Learning Problems.
Proceedings of the 2nd International Conference on Learning Representations, 2014

A variational approach to stable principal component pursuit.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

A new kernel-based approach for identification of time-varying linear systems.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Kalman smoothing with persistent nuisance parameters.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Orthogonal Matching Pursuit for Sparse Quantile Regression.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Iterative log thresholding.
Proceedings of the IEEE International Conference on Acoustics, 2014

Smoothing dynamic systems with state-dependent covariance matrices.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

ALETHEIA: Improving the Usability of Static Security Analysis.
Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, 2014

2013
Variational Properties of Value Functions.
SIAM J. Optim., 2013

Sparse/robust estimation and Kalman smoothing with nonsmooth log-concave densities: modeling, computation, and theory.
J. Mach. Learn. Res., 2013

An SVD-free Pareto curve approach to rank minimization
CoRR, 2013

The exact relationship between regularization in RKHS and Bayesian estimation of Gaussian random fields
CoRR, 2013

Improving training time of Hessian-free optimization for deep neural networks using preconditioning and sampling.
CoRR, 2013

Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models.
Proceedings of the 30th International Conference on Machine Learning, 2013

Sparse seismic imaging using variable projection.
Proceedings of the IEEE International Conference on Acoustics, 2013

Linear system identification using stable spline kernels and PLQ penalties.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Improvements to Deep Convolutional Neural Networks for LVCSR.
Proceedings of the 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 2013

Accelerating Hessian-free optimization for Deep Neural Networks by implicit preconditioning and sampling.
Proceedings of the 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 2013

2012
Robust inversion, dimensionality reduction, and randomized sampling.
Math. Program., 2012

Student's t robust bundle adjustment algorithm.
Proceedings of the 19th IEEE International Conference on Image Processing, 2012

Fast seismic imaging for marine data.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Robust inversion via semistochastic dimensionality reduction.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Nonsmooth regression and state estimation using piecewise quadratic log-concave densities.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

2011
An <sub>1</sub> -Laplace Robust Kalman Smoother.
IEEE Trans. Autom. Control., 2011

Convex vs nonconvex approaches for sparse estimation: Lasso, Multiple Kernel Learning and Hyperparameter Lasso.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010
The unconstrained and inequality constrained moving horizon approach to robot localization.
Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010


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