The unconstrained and inequality constrained moving horizon approach to robot localization. - Gianluigi Pillonetto; Aleksandr Y. Aravkin; Stefano Carpin (IROS, 2010)

Convex vs nonconvex approaches for sparse estimation: Lasso, Multiple Kernel Learning and Hyperparameter Lasso. - Aleksandr Y. Aravkin; James V. Burke; Alessandro Chiuso; Gianluigi Pillonetto (CDC/ECC, 2011)

An 1 -Laplace Robust Kalman Smoother. - Aleksandr Y. Aravkin; Bradley M. Bell; James V. Burke; Gianluigi Pillonetto (IEEE Trans. Autom. Control., 2011)

Nonsmooth regression and state estimation using piecewise quadratic log-concave densities. - Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto (CDC, 2012)

Robust inversion via semistochastic dimensionality reduction. - Aleksandr Y. Aravkin; Michael P. Friedlander; Tristan van Leeuwen (ICASSP, 2012)

Fast seismic imaging for marine data. - Aleksandr Y. Aravkin; Xiang Li; Felix J. Herrmann (ICASSP, 2012)

Student's t robust bundle adjustment algorithm. - Aleksandr Y. Aravkin; Michael Styer; Zachary Moratto; Ara V. Nefian; Michael Broxton (ICIP, 2012)

Robust inversion, dimensionality reduction, and randomized sampling. - Aleksandr Y. Aravkin; Michael P. Friedlander; Felix J. Herrmann; Tristan van Leeuwen (Math. Program., 2012)

Accelerating Hessian-free optimization for Deep Neural Networks by implicit preconditioning and sampling. - Tara N. Sainath; Lior Horesh; Brian Kingsbury; Aleksandr Y. Aravkin; Bhuvana Ramabhadran (ASRU, 2013)

Improvements to Deep Convolutional Neural Networks for LVCSR. - Tara N. Sainath; Brian Kingsbury; Abdel-rahman Mohamed; George E. Dahl; George Saon; Hagen Soltau; Tomás Beran; Aleksandr Y. Aravkin; Bhuvana Ramabhadran (ASRU, 2013)

Linear system identification using stable spline kernels and PLQ penalties. - Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto (CDC, 2013)

Sparse seismic imaging using variable projection. - Aleksandr Y. Aravkin; Tristan van Leeuwen; Ning Tu (ICASSP, 2013)

Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models. - Mohammad Emtiyaz Khan; Aleksandr Y. Aravkin; Michael P. Friedlander; Matthias W. Seeger (ICML (3), 2013)

Improving training time of Hessian-free optimization for deep neural networks using preconditioning and sampling. - Tara N. Sainath; Lior Horesh; Brian Kingsbury; Aleksandr Y. Aravkin; Bhuvana Ramabhadran (CoRR, 2013)

The exact relationship between regularization in RKHS and Bayesian estimation of Gaussian random fields - Aleksandr Y. Aravkin; Bradley M. Bell; James V. Burke; Gianluigi Pillonetto (CoRR, 2013)

An SVD-free Pareto curve approach to rank minimization - Aleksandr Y. Aravkin; Rajiv Mittal; Hassan Mansour; Ben Recht; Felix J. Herrmann (CoRR, 2013)

Sparse/robust estimation and Kalman smoothing with nonsmooth log-concave densities: modeling, computation, and theory. - Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto (J. Mach. Learn. Res., 2013)

Variational Properties of Value Functions. - Aleksandr Y. Aravkin; James V. Burke; Michael P. Friedlander (SIAM J. Optim., 2013)

ALETHEIA: Improving the Usability of Static Security Analysis. - Omer Tripp; Salvatore Guarnieri; Marco Pistoia; Aleksandr Y. Aravkin (CCS, 2014)

Smoothing dynamic systems with state-dependent covariance matrices. - Aleksandr Y. Aravkin; James V. Burke (CDC, 2014)

Iterative log thresholding. - Dmitry Malioutov; Aleksandr Y. Aravkin (ICASSP, 2014)

Orthogonal Matching Pursuit for Sparse Quantile Regression. - Aleksandr Y. Aravkin; Aurélie C. Lozano; Ronny Luss; Prabhanjan Kambadur (ICDM, 2014)

Kalman smoothing with persistent nuisance parameters. - Aleksandr Y. Aravkin; Karthikeyan Natesan Ramamurthy; Gianluigi Pillonetto (MLSP, 2014)

A new kernel-based approach for identification of time-varying linear systems. - Gianluigi Pillonetto; Aleksandr Y. Aravkin (MLSP, 2014)

A variational approach to stable principal component pursuit. - Aleksandr Y. Aravkin; Stephen Becker; Volkan Cevher; Peder A. Olsen (UAI, 2014)

Semistochastic Quadratic Bound Methods for Convex and Nonconvex Learning Problems. - Aleksandr Y. Aravkin; Anna Choromanska; Dimitri Kanevsky; Tony Jebara (ICLR (Workshop Poster), 2014)

Sparse Quantile Huber Regression for Efficient and Robust Estimation. - Aleksandr Y. Aravkin; Anju Kambadur; Aurélie C. Lozano; Ronny Luss (CoRR, 2014)

Convex vs non-convex estimators for regression and sparse estimation: the mean squared error properties of ARD and GLasso. - Aleksandr Y. Aravkin; James V. Burke; Alessandro Chiuso; Gianluigi Pillonetto (J. Mach. Learn. Res., 2014)

Robust and Trend-Following Student's t Kalman Smoothers. - Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto (SIAM J. Control. Optim., 2014)

Fast Methods for Denoising Matrix Completion Formulations, with Applications to Robust Seismic Data Interpolation. - Aleksandr Y. Aravkin; Rajiv Kumar 003; Hassan Mansour; Ben Recht; Felix J. Herrmann (SIAM J. Sci. Comput., 2014)

Outlier robust kernel-based system identification using ℓ1-Laplace techniques. - Giulio Bottegal; Håkan Hjalmarsson; Aleksandr Y. Aravkin; Gianluigi Pillonetto (CDC, 2015)

Adaptive as-natural-as-possible image stitching. - Chung-Ching Lin; Sharathchandra Pankanti; Karthikeyan Natesan Ramamurthy; Aleksandr Y. Aravkin (CVPR, 2015)

Source estimation for wave equations with uncertain parameters. - Sergiy Zhuk; Stephen Moore 003; Alberto Costa Nogueira Jr.; Andrew A. Rawlinson; Tigran T. Tchrakian; Lior Horesh; Aleksandr Y. Aravkin; Albert Akhriev (ECC, 2015)

The Connection Between Bayesian Estimation of a Gaussian Random Field and RKHS. - Aleksandr Y. Aravkin; Bradley M. Bell; James V. Burke; Gianluigi Pillonetto (IEEE Trans. Neural Networks Learn. Syst., 2015)

Beyond L2-loss functions for learning sparse models. - Karthikeyan Natesan Ramamurthy; Aleksandr Y. Aravkin; Jayaraman J. Thiagarajan (ICASSP, 2016)

Dynamic matrix factorization with social influence. - Aleksandr Y. Aravkin; Kush R. Varshney; Liu Yang (MLSP, 2016)

A stable spline convex approach to hybrid systems identification. - Gianluigi Pillonetto; Aleksandr Y. Aravkin (MLSP, 2016)

Robust EM kernel-based methods for linear system identification. - Giulio Bottegal; Aleksandr Y. Aravkin; Håkan Hjalmarsson; Gianluigi Pillonetto (Autom., 2016)

Dual Smoothing and Level Set Techniques for Variational Matrix Decomposition. - Aleksandr Y. Aravkin; Stephen Becker (CoRR, 2016)

A SMART Stochastic Algorithm for Nonconvex Optimization with Applications to Robust Machine Learning. - Aleksandr Y. Aravkin; Damek Davis (CoRR, 2016)

Analytics for understanding customer behavior in the energy and utility industry. - Younghun Kim; Aleksandr Y. Aravkin; Hongliang Fei; A. Zondervan; M. Wolf (IBM J. Res. Dev., 2016)

Distributed Bundle Adjustment. - Karthikeyan Natesan Ramamurthy; Chung-Ching Lin; Aleksandr Y. Aravkin; Sharath Pankanti; Raphael Viguier (ICCV Workshops, 2017)

Learning Robust Representations for Computer Vision. - Peng Zheng 002; Aleksandr Y. Aravkin; Jayaraman J. Thiagarajan; Karthikeyan Natesan Ramamurthy (ICCV Workshops, 2017)

Generalized Kalman smoothing: Modeling and algorithms. - Aleksandr Y. Aravkin; James V. Burke; Lennart Ljung; Aurélie C. Lozano; Gianluigi Pillonetto (Autom., 2017)

Beating Level-Set Methods for 5-D Seismic Data Interpolation: A Primal-Dual Alternating Approach. - Rajiv Kumar 003; Oscar López; Damek Davis; Aleksandr Y. Aravkin; Felix J. Herrmann (IEEE Trans. Computational Imaging, 2017)

Mean Reverting Portfolios via Penalized OU-Likelihood Estimation. - Jize Zhang; Tim Leung; Aleksandr Y. Aravkin (CDC, 2018)

Sparse Principal Component Analysis via Variable Projection. - N. Benjamin Erichson; Peng Zeng; Krithika Manohar; Steven L. Brunton; J. Nathan Kutz; Aleksandr Y. Aravkin (CoRR, 2018)

Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM. - Germán Abrevaya; Aleksandr Y. Aravkin; Guillermo A. Cecchi; Irina Rish; Pablo Polosecki; Peng Zheng 002; Silvina Ponce Dawson (CoRR, 2018)

Sparse Relaxed Regularized Regression: SR3. - Peng Zheng 002; Travis Askham; Steven L. Brunton; J. Nathan Kutz; Aleksandr Y. Aravkin (CoRR, 2018)

Total Variation Regularization Strategies in Full-Waveform Inversion. - Ernie Esser; Lluís Guasch; Tristan van Leeuwen; Aleksandr Y. Aravkin; Felix J. Herrmann (SIAM J. Imaging Sci., 2018)

Foundations of Gauge and Perspective Duality. - Aleksandr Y. Aravkin; James V. Burke; Dmitriy Drusvyatskiy; Michael P. Friedlander; Kellie J. MacPhee (SIAM J. Optim., 2018)

Generalized System Identification with Stable Spline Kernels. - Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto (SIAM J. Sci. Comput., 2018)

Efficient Quadratic Penalization Through the Partial Minimization Technique. - Aleksandr Y. Aravkin; Dmitriy Drusvyatskiy; Tristan van Leeuwen (IEEE Trans. Autom. Control., 2018)

A Relaxed Optimization Approach for Cardinality-Constrained Portfolios. - Jize Zhang; Tim Leung; Aleksandr Y. Aravkin (ECC, 2019)

Trimming the $ ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning. - Jihun Yun; Peng Zheng 002; Eunho Yang; Aurélie C. Lozano; Aleksandr Y. Aravkin (ICML, 2019)

Robust Singular Smoothers for Tracking Using Low-Fidelity Data. - Jonathan Jonker; Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto; Sarah E. Webster (Robotics: Science and Systems, 2019)

A Unified Framework for Sparse Relaxed Regularized Regression: SR3. - Peng Zheng 002; Travis Askham; Steven L. Brunton; J. Nathan Kutz; Aleksandr Y. Aravkin (IEEE Access, 2019)

Fast robust methods for singular state-space models. - Jonathan Jonker; Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto; Sarah E. Webster (Autom., 2019)

Boosting as a kernel-based method. - Aleksandr Y. Aravkin; Giulio Bottegal; Gianluigi Pillonetto (Mach. Learn., 2019)

Level-set methods for convex optimization. - Aleksandr Y. Aravkin; James V. Burke; Dmitriy Drusvyatskiy; Michael P. Friedlander; Scott Roy (Math. Program., 2019)

Adapting Regularized Low-Rank Models for Parallel Architectures. - Derek Driggs; Stephen Becker; Aleksandr Y. Aravkin (SIAM J. Sci. Comput., 2019)

Basis Pursuit Denoise With Nonsmooth Constraints. - Robert J. Baraldi; Rajiv Kumar 003; Aleksandr Y. Aravkin (IEEE Trans. Signal Process., 2019)

A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data. - Kathleen P. Champion; Peng Zheng 002; Aleksandr Y. Aravkin; Steven L. Brunton; J. Nathan Kutz (IEEE Access, 2020)

Sparse mean-reverting portfolios via penalized likelihood optimization. - Jize Zhang; Tim Leung; Aleksandr Y. Aravkin (Autom., 2020)

Offline state estimation for hybrid systems via nonsmooth variable projection. - Jize Zhang; Andrew M. Pace; Samuel A. Burden; Aleksandr Y. Aravkin (Autom., 2020)

Physics-informed machine learning for sensor fault detection with flight test data. - Brian M. de Silva; Jared Callaham; Jonathan Jonker; Nicholas Goebel; Jennifer Klemisch; Darren McDonald; Nathan Hicks; J. Nathan Kutz; Steven L. Brunton; Aleksandr Y. Aravkin (CoRR, 2020)

Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning. - Steven L. Brunton; J. Nathan Kutz; Krithika Manohar; Aleksandr Y. Aravkin; Kristi Morgansen; Jennifer Klemisch; Nicholas Goebel; James Buttrick; Jeffrey Poskin; Agnes Blom-Schieber; Thomas A. Hogan; Darren McDonald (CoRR, 2020)

Trimmed Statistical Estimation via Variance Reduction. - Aleksandr Y. Aravkin; Damek Davis (Math. Oper. Res., 2020)

Sparse Principal Component Analysis via Variable Projection. - N. Benjamin Erichson; Peng Zheng 002; Krithika Manohar; Steven L. Brunton; J. Nathan Kutz; Aleksandr Y. Aravkin (SIAM J. Appl. Math., 2020)

Stable and robust LQR design via scenario approach. - Anna Scampicchio; Aleksandr Y. Aravkin; Gianluigi Pillonetto (Autom., 2021)

Analysis of Truncated Orthogonal Iteration for Sparse Eigenvector Problems. - Hexuan Liu; Aleksandr Y. Aravkin (CoRR, 2021)

A feasibility study of a hyperparameter tuning approach to automated inverse planning in radiotherapy. - Kelsey Maass; Aleksandr Y. Aravkin; Minsun Kim (CoRR, 2021)

Theoretical Advances in Current Estimation and Navigation from a Glider-Based Acoustic Doppler Current Profiler (ADCP). - Jacob Stevens-Haas; Sarah E. Webster; Aleksandr Y. Aravkin (CoRR, 2021)

Trimmed Constrained Mixed Effects Models: Formulations and Algorithms. - Peng Zheng 002; Ryan Barber; Reed J. D. Sorensen; Christopher J. L. Murray; Aleksandr Y. Aravkin (J. Comput. Graph. Stat., 2021)

Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. - Germán Abrevaya; Guillaume Dumas; Aleksandr Y. Aravkin; Peng Zheng 002; Jean-Christophe Gagnon-Audet; James R. Kozloski; Pablo Polosecki; Guillaume Lajoie; David D. Cox; Silvina Ponce Dawson; Guillermo A. Cecchi; Irina Rish (Neural Comput., 2021)

Estimating Shape Parameters of Piecewise Linear-Quadratic Problems. - Peng Zheng 002; Karthikeyan Natesan Ramamurthy; Aleksandr Y. Aravkin (Open J. Math. Optim., 2021)

Time-Varying Autoregression with Low-Rank Tensors. - Kameron Decker Harris; Aleksandr Y. Aravkin; Rajesh Rao; Bingni Wen Brunton (SIAM J. Appl. Dyn. Syst., 2021)

Variable Projection for NonSmooth Problems. - Tristan van Leeuwen; Aleksandr Y. Aravkin (SIAM J. Sci. Comput., 2021)

$ ell _{1}$-Norm Minimization With Regula Falsi Type Root Finding Methods. - Metin Vural; Aleksandr Y. Aravkin; Slawomir Stanczak (IEEE Signal Process. Lett., 2021)

Efficient Robust Parameter Identification in Generalized Kalman Smoothing Models. - Jonathan Jonker; Peng Zheng 002; Aleksandr Y. Aravkin (IEEE Trans. Autom. Control., 2021)

On the Global Minimizers of Real Robust Phase Retrieval With Sparse Noise. - Aleksandr Y. Aravkin; James V. Burke; Daiwei He (IEEE Trans. Inf. Theory, 2021)

Spatiotemporal k-means. - Olga Dorabiala; Jennifer Webster; J. Nathan Kutz; Aleksandr Y. Aravkin (CoRR, 2022)

A Nonconvex Optimization Approach to IMRT Planning with Dose-Volume Constraints. - Kelsey Maass; Minsun Kim; Aleksandr Y. Aravkin (INFORMS J. Comput., 2022)

Robust trimmed k-means. - Olga Dorabiala; J. Nathan Kutz; Aleksandr Y. Aravkin (Pattern Recognit. Lett., 2022)

Robust and Scalable Methods for the Dynamic Mode Decomposition. - Travis Askham; Peng Zheng 002; Aleksandr Y. Aravkin; J. Nathan Kutz (SIAM J. Appl. Dyn. Syst., 2022)

A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimization. - Aleksandr Y. Aravkin; Robert J. Baraldi; Dominique Orban (SIAM J. Optim., 2022)

pysr3: A Python Package for Sparse Relaxed Regularized Regression. - Aleksei Sholokhov; Peng Zheng 002; Aleksandr Y. Aravkin (J. Open Source Softw., 2023)

Ensemble Principal Component Analysis. - Olga Dorabiala; Aleksandr Y. Aravkin; J. Nathan Kutz (IEEE Access, 2024)

Learning Nonlinear Dynamics Using Kalman Smoothing. - Jacob Stevens-Haas; Yash Bhangale; J. Nathan Kutz; Aleksandr Y. Aravkin (IEEE Access, 2024)

Uncertainty Quantification under Noisy Constraints, with Applications to Raking. - Ariane Ducellier; Alexander Hsu; Parkes Kendrick; Bill Gustafson; Laura Dwyer-Lindgren; Christopher Murray; Peng Zheng 002; Aleksandr Y. Aravkin (CoRR, 2024)

A Relaxation Approach to Feature Selection for Linear Mixed Effects Models. - Aleksei Sholokhov; James V. Burke; Damian F. Santomauro; Peng Zheng 002; Aleksandr Y. Aravkin (J. Comput. Graph. Stat., 2024)

A Levenberg-Marquardt Method for Nonsmooth Regularized Least Squares. - Aleksandr Y. Aravkin; Robert J. Baraldi; Dominique Orban (SIAM J. Sci. Comput., 2024)

Deep networks for system identification: A survey. - Gianluigi Pillonetto; Aleksandr Y. Aravkin; Daniel Gedon; Lennart Ljung; Antônio H. Ribeiro; Thomas B. Schön (Autom., 2025)

Fitting dynamic measles models to subnational case notification data from Ethiopia: Methodological challenges and key considerations. - Alyssa N. Sbarra; Emily Haeuser; Samuel Kidane; Andargie Abate; Ayele M. Abebe; Muktar Ahmed; Alemayehu Tsegaye; Erkihun Amsalu; Aleksandr Y. Aravkin; Akeza A. Asgedom; Nebiyou Bayleyegn; Mulat Dagnew; et al. (PLoS Comput. Biol., 2025)

Sparse-mode Dynamic Mode Decomposition for Disambiguating Local and Global Structures. - Sara M. Ichinaga; Steven L. Brunton; Aleksandr Y. Aravkin; J. Nathan Kutz (CoRR, 2025)