Aleksandr Y. Aravkin

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 68

Top Venues

Publications

Olga Dorabiala, Aleksandr Y. Aravkin, J. Nathan Kutz
Ensemble Principal Component Analysis. IEEE Access 12 (2024)
Aleksei Sholokhov, Peng Zheng, Aleksandr Y. Aravkin
pysr3: A Python Package for Sparse Relaxed Regularized Regression. J. Open Source Softw. 8 (86) (2023)
Gianluigi Pillonetto, Aleksandr Y. Aravkin, Daniel Gedon, Lennart Ljung, Antônio H. Ribeiro, Thomas B. Schön
Deep networks for system identification: a Survey. CoRR (2023)
Aleksandr Y. Aravkin, Robert Baraldi, Dominique Orban
A Levenberg-Marquardt Method for Nonsmooth Regularized Least Squares. CoRR (2023)
Olga Dorabiala, Jennifer Webster, J. Nathan Kutz, Aleksandr Y. Aravkin
Spatiotemporal k-means. CoRR (2022)
Travis Askham, Peng Zheng, Aleksandr Y. Aravkin, J. Nathan Kutz
Robust and Scalable Methods for the Dynamic Mode Decomposition. SIAM J. Appl. Dyn. Syst. 21 (1) (2022)
Olga Dorabiala, J. Nathan Kutz, Aleksandr Y. Aravkin
Robust trimmed k-means. Pattern Recognit. Lett. 161 (2022)
Kelsey Maass, Minsun Kim, Aleksandr Y. Aravkin
A Nonconvex Optimization Approach to IMRT Planning with Dose-Volume Constraints. INFORMS J. Comput. 34 (3) (2022)
Aleksandr Y. Aravkin, Robert Baraldi, Dominique Orban
A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimization. SIAM J. Optim. 32 (2) (2022)
Olga Dorabiala, J. Nathan Kutz, Aleksandr Y. Aravkin
Robust Trimmed k-means. CoRR (2021)
Jacob Stevens-Haas, Sarah E. Webster, Aleksandr Y. Aravkin
Theoretical Advances in Current Estimation and Navigation from a Glider-Based Acoustic Doppler Current Profiler (ADCP). CoRR (2021)
German Abrevaya, Guillaume Dumas, Aleksandr Y. Aravkin, Peng Zheng, Jean-Christophe Gagnon-Audet, James R. Kozloski, Pablo Polosecki, Guillaume Lajoie, David D. Cox, Silvina Ponce Dawson, Guillermo A. Cecchi, Irina Rish
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. Neural Comput. 33 (8) (2021)
Tristan van Leeuwen, Aleksandr Y. Aravkin
Variable Projection for NonSmooth Problems. SIAM J. Sci. Comput. 43 (5) (2021)
Peng Zheng, Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin
Estimating Shape Parameters of Piecewise Linear-Quadratic Problems. Open J. Math. Optim. 2 (2021)
Kameron Decker Harris, Aleksandr Y. Aravkin, Rajesh Rao, Bingni Wen Brunton
Time-Varying Autoregression with Low-Rank Tensors. SIAM J. Appl. Dyn. Syst. 20 (4) (2021)
Kelsey Maass, Aleksandr Y. Aravkin, Minsun Kim
A feasibility study of a hyperparameter tuning approach to automated inverse planning in radiotherapy. CoRR (2021)
Hexuan Liu, Aleksandr Y. Aravkin
Analysis of Truncated Orthogonal Iteration for Sparse Eigenvector Problems. CoRR (2021)
Peng Zheng, Ryan Barber, Reed J. D. Sorensen, Christopher J. L. Murray, Aleksandr Y. Aravkin
Trimmed Constrained Mixed Effects Models: Formulations and Algorithms. J. Comput. Graph. Stat. 30 (3) (2021)
Anna Scampicchio, Aleksandr Y. Aravkin, Gianluigi Pillonetto
Stable and robust LQR design via scenario approach. Autom. 129 (2021)
Aleksandr Y. Aravkin, James V. Burke, Daiwei He
On the Global Minimizers of Real Robust Phase Retrieval With Sparse Noise. IEEE Trans. Inf. Theory 67 (3) (2021)
Jonathan Jonker, Peng Zheng, Aleksandr Y. Aravkin
Efficient Robust Parameter Identification in Generalized Kalman Smoothing Models. IEEE Trans. Autom. Control. 66 (10) (2021)
Metin Vural, Aleksandr Y. Aravkin, Slawomir Stanczak
$\ell _{1}$-Norm Minimization With Regula Falsi Type Root Finding Methods. IEEE Signal Process. Lett. 28 (2021)
Jize Zhang, Tim Leung, Aleksandr Y. Aravkin
Sparse mean-reverting portfolios via penalized likelihood optimization. Autom. 111 (2020)
N. Benjamin Erichson, Peng Zheng, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
Sparse Principal Component Analysis via Variable Projection. SIAM J. Appl. Math. 80 (2) (2020)
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
Physics-informed machine learning for sensor fault detection with flight test data. CoRR (2020)
Kathleen P. Champion, Peng Zheng, Aleksandr Y. Aravkin, Steven L. Brunton, J. Nathan Kutz
A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data. IEEE Access 8 (2020)
Aleksandr Y. Aravkin, Damek Davis
Trimmed Statistical Estimation via Variance Reduction. Math. Oper. Res. 45 (1) (2020)
Jize Zhang, Andrew M. Pace, Samuel A. Burden, Aleksandr Y. Aravkin
Offline state estimation for hybrid systems via nonsmooth variable projection. Autom. 115 (2020)
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
Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning. CoRR (2020)
Jonathan Jonker, Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, Sarah E. Webster
Fast robust methods for singular state-space models. Autom. 105 (2019)
Aleksandr Y. Aravkin, James V. Burke, Daiwei He
On the Global Minimizers of Real Robust Phase Retrieval with Sparse Noise. CoRR (2019)
Robert Baraldi, Rajiv Kumar, Aleksandr Y. Aravkin
Basis Pursuit Denoise With Nonsmooth Constraints. IEEE Trans. Signal Process. 67 (22) (2019)
Jonathan Jonker, Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, Sarah E. Webster
Robust Singular Smoothers for Tracking Using Low-Fidelity Data. Robotics: Science and Systems (2019)
Derek Driggs, Stephen Becker, Aleksandr Y. Aravkin
Adapting Regularized Low-Rank Models for Parallel Architectures. SIAM J. Sci. Comput. 41 (1) (2019)
Kathleen P. Champion, Peng Zheng, Aleksandr Y. Aravkin, Steven L. Brunton, J. Nathan Kutz
A unified sparse optimization framework to learn parsimonious physics-informed models from data. CoRR (2019)
Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy
Level-set methods for convex optimization. Math. Program. 174 (1-2) (2019)
Peng Zheng, Travis Askham, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
A Unified Framework for Sparse Relaxed Regularized Regression: SR3. IEEE Access 7 (2019)
Jihun Yun, Peng Zheng, Eunho Yang, Aurelie C. Lozano, Aleksandr Y. Aravkin
Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning. ICML (2019)
Aleksandr Y. Aravkin, Giulio Bottegal, Gianluigi Pillonetto
Boosting as a kernel-based method. Mach. Learn. 108 (11) (2019)
Jize Zhang, Tim Leung, Aleksandr Y. Aravkin
A Relaxed Optimization Approach for Cardinality-Constrained Portfolios. ECC (2019)
Kameron Decker Harris, Aleksandr Y. Aravkin, Rajesh Rao, Bingni Wen Brunton
Time-varying Autoregression with Low Rank Tensors. CoRR (2019)
Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Kellie J. MacPhee
Foundations of Gauge and Perspective Duality. SIAM J. Optim. 28 (3) (2018)
Peng Zheng, Travis Askham, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
Sparse Relaxed Regularized Regression: SR3. CoRR (2018)
German Abrevaya, Aleksandr Y. Aravkin, Guillermo A. Cecchi, Irina Rish, Pablo Polosecki, Peng Zheng, Silvina Ponce Dawson
Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM. CoRR (2018)
Aleksandr Y. Aravkin, Dmitriy Drusvyatskiy, Tristan van Leeuwen
Efficient Quadratic Penalization Through the Partial Minimization Technique. IEEE Trans. Autom. Control. 63 (7) (2018)
Ernie Esser, Lluis Guasch, Tristan van Leeuwen, Aleksandr Y. Aravkin, Felix J. Herrmann
Total Variation Regularization Strategies in Full-Waveform Inversion. SIAM J. Imaging Sci. 11 (1) (2018)
Jize Zhang, Tim Leung, Aleksandr Y. Aravkin
Mean Reverting Portfolios via Penalized OU-Likelihood Estimation. CDC (2018)
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Generalized System Identification with Stable Spline Kernels. SIAM J. Sci. Comput. 40 (5) (2018)
N. Benjamin Erichson, Peng Zeng, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
Sparse Principal Component Analysis via Variable Projection. CoRR (2018)
Aleksandr Y. Aravkin, James V. Burke, Lennart Ljung, Aurelie C. Lozano, Gianluigi Pillonetto
Generalized Kalman smoothing: Modeling and algorithms. Autom. 86 (2017)
Karthikeyan Natesan Ramamurthy, Chung-Ching Lin, Aleksandr Y. Aravkin, Sharath Pankanti, Raphael Viguier
Distributed Bundle Adjustment. ICCV Workshops (2017)
Karthikeyan Natesan Ramamurthy, Chung-Ching Lin, Aleksandr Y. Aravkin, Sharath Pankanti, Raphael Viguier
Distributed Bundle Adjustment. CoRR (2017)
Rajiv Kumar, Oscar Lopez, Damek Davis, Aleksandr Y. Aravkin, Felix J. Herrmann
Beating Level-Set Methods for 5-D Seismic Data Interpolation: A Primal-Dual Alternating Approach. IEEE Trans. Computational Imaging 3 (2) (2017)
Peng Zheng, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy
Learning Robust Representations for Computer Vision. ICCV Workshops (2017)
Peng Zheng, Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan
Learning Robust Representations for Computer Vision. CoRR (2017)
Aleksandr Y. Aravkin, Kush R. Varshney, Liu Yang
Dynamic matrix factorization with social influence. MLSP (2016)
Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy
Level-set methods for convex optimization. CoRR (2016)
Aleksandr Y. Aravkin, Damek Davis
A SMART Stochastic Algorithm for Nonconvex Optimization with Applications to Robust Machine Learning. CoRR (2016)
Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan
Beyond L2-loss functions for learning sparse models. ICASSP (2016)
Aleksandr Y. Aravkin, Kush R. Varshney, Liu Yang
Dynamic matrix factorization with social influence. CoRR (2016)
Giulio Bottegal, Aleksandr Y. Aravkin, Håkan Hjalmarsson, Gianluigi Pillonetto
Robust EM kernel-based methods for linear system identification. Autom. 67 (2016)
Younghun Kim, Aleksandr Y. Aravkin, Hongliang Fei, A. Zondervan, M. Wolf
Analytics for understanding customer behavior in the energy and utility industry. IBM J. Res. Dev. 60 (1) (2016)
Gianluigi Pillonetto, Aleksandr Y. Aravkin
A stable spline convex approach to hybrid systems identification. MLSP (2016)
Aleksandr Y. Aravkin, Stephen Becker
Dual Smoothing and Level Set Techniques for Variational Matrix Decomposition. CoRR (2016)
Giulio Bottegal, Håkan Hjalmarsson, Aleksandr Y. Aravkin, Gianluigi Pillonetto
Outlier robust kernel-based system identification using ℓ1-Laplace techniques. CDC (2015)
Sergiy Zhuk, Stephen Moore, Alberto Costa Nogueira Jr., Andrew A. Rawlinson, Tigran T. Tchrakian, Lior Horesh, Aleksandr Y. Aravkin, Albert Akhriev
Source estimation for wave equations with uncertain parameters. ECC (2015)
Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto
The Connection Between Bayesian Estimation of a Gaussian Random Field and RKHS. IEEE Trans. Neural Networks Learn. Syst. 26 (7) (2015)
Chung-Ching Lin, Sharathchandra Pankanti, Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin
Adaptive as-natural-as-possible image stitching. CVPR (2015)
Dmitry Malioutov, Aleksandr Y. Aravkin
Iterative log thresholding. ICASSP (2014)
Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan
Beyond L2-Loss Functions for Learning Sparse Models. CoRR (2014)
Aleksandr Y. Aravkin, Rajiv Kumar, Hassan Mansour, Ben Recht, Felix J. Herrmann
Fast Methods for Denoising Matrix Completion Formulations, with Applications to Robust Seismic Data Interpolation. SIAM J. Sci. Comput. 36 (5) (2014)
Aleksandr Y. Aravkin, Stephen Becker, Volkan Cevher, Peder A. Olsen
A variational approach to stable principal component pursuit. UAI (2014)
Giulio Bottegal, Aleksandr Y. Aravkin, Håkan Hjalmarsson, Gianluigi Pillonetto
Robust EM kernel-based methods for linear system identification. CoRR (2014)
Aleksandr Y. Aravkin, Anju Kambadur, Aurelie C. Lozano, Ronny Luss
Sparse Quantile Huber Regression for Efficient and Robust Estimation. CoRR (2014)
Aleksandr Y. Aravkin, Anna Choromanska, Dimitri Kanevsky, Tony Jebara
Semistochastic Quadratic Bound Methods for Convex and Nonconvex Learning Problems. ICLR (Workshop Poster) (2014)
Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy, Gianluigi Pillonetto
Kalman smoothing with persistent nuisance parameters. MLSP (2014)
Gianluigi Pillonetto, Aleksandr Y. Aravkin
A new kernel-based approach for identification of time-varying linear systems. MLSP (2014)
Omer Tripp, Salvatore Guarnieri, Marco Pistoia, Aleksandr Y. Aravkin
ALETHEIA: Improving the Usability of Static Security Analysis. CCS (2014)
Aleksandr Y. Aravkin, James V. Burke
Smoothing dynamic systems with state-dependent covariance matrices. CDC (2014)
Aleksandr Y. Aravkin, Aurelie C. Lozano, Ronny Luss, Prabhanjan Kambadur
Orthogonal Matching Pursuit for Sparse Quantile Regression. ICDM (2014)
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Robust and Trend-Following Student's t Kalman Smoothers. SIAM J. Control. Optim. 52 (5) (2014)
Aleksandr Y. Aravkin, James V. Burke, Alessandro Chiuso, Gianluigi Pillonetto
Convex vs non-convex estimators for regression and sparse estimation: the mean squared error properties of ARD and GLasso. J. Mach. Learn. Res. 15 (1) (2014)
Mohammad Emtiyaz Khan, Aleksandr Y. Aravkin, Michael P. Friedlander, Matthias W. Seeger
Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models. ICML (3) (2013)
Tara N. Sainath, Lior Horesh, Brian Kingsbury, Aleksandr Y. Aravkin, Bhuvana Ramabhadran
Improving training time of Hessian-free optimization for deep neural networks using preconditioning and sampling. CoRR (2013)
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Linear system identification using stable spline kernels and PLQ penalties. CDC (2013)
Aleksandr Y. Aravkin, James V. Burke, Michael P. Friedlander
Variational Properties of Value Functions. SIAM J. Optim. 23 (3) (2013)
Tara N. Sainath, Brian Kingsbury, Abdel-rahman Mohamed, George E. Dahl, George Saon, Hagen Soltau, Tomás Beran, Aleksandr Y. Aravkin, Bhuvana Ramabhadran
Improvements to deep convolutional neural networks for LVCSR. CoRR (2013)
Aleksandr Y. Aravkin, Rajiv Mittal, Hassan Mansour, Ben Recht, Felix J. Herrmann
An SVD-free Pareto curve approach to rank minimization CoRR (2013)
Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto
The exact relationship between regularization in RKHS and Bayesian estimation of Gaussian random fields CoRR (2013)
Tara N. Sainath, Brian Kingsbury, Abdel-rahman Mohamed, George E. Dahl, George Saon, Hagen Soltau, Tomás Beran, Aleksandr Y. Aravkin, Bhuvana Ramabhadran
Improvements to Deep Convolutional Neural Networks for LVCSR. ASRU (2013)
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Sparse/robust estimation and Kalman smoothing with nonsmooth log-concave densities: modeling, computation, and theory. J. Mach. Learn. Res. 14 (1) (2013)
Aleksandr Y. Aravkin, Tristan van Leeuwen, Ning Tu
Sparse seismic imaging using variable projection. ICASSP (2013)
Tara N. Sainath, Lior Horesh, Brian Kingsbury, Aleksandr Y. Aravkin, Bhuvana Ramabhadran
Accelerating Hessian-free optimization for Deep Neural Networks by implicit preconditioning and sampling. ASRU (2013)
Aleksandr Y. Aravkin, Michael P. Friedlander, Tristan van Leeuwen
Robust inversion via semistochastic dimensionality reduction. ICASSP (2012)
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Nonsmooth regression and state estimation using piecewise quadratic log-concave densities. CDC (2012)
Aleksandr Y. Aravkin, Xiang Li, Felix J. Herrmann
Fast seismic imaging for marine data. ICASSP (2012)
Aleksandr Y. Aravkin, Michael P. Friedlander, Felix J. Herrmann, Tristan van Leeuwen
Robust inversion, dimensionality reduction, and randomized sampling. Math. Program. 134 (1) (2012)
Aleksandr Y. Aravkin, Michael Styer, Zachary Moratto, Ara V. Nefian, Michael Broxton
Student's t robust bundle adjustment algorithm. ICIP (2012)
Aleksandr Y. Aravkin, Michael P. Friedlander, Tristan van Leeuwen
Robust inversion via semistochastic dimensionality reduction CoRR (2011)
Aleksandr Y. Aravkin, James V. Burke, Alessandro Chiuso, Gianluigi Pillonetto
Convex vs nonconvex approaches for sparse estimation: Lasso, Multiple Kernel Learning and Hyperparameter Lasso. CDC/ECC (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Aleksandr Y. Aravkin