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2020 – today
- 2025
[j46]Gianluigi Pillonetto, Aleksandr Y. Aravkin, Daniel Gedon, Lennart Ljung, Antônio H. Ribeiro, Thomas B. Schön:
Deep networks for system identification: A survey. Autom. 171: 111907 (2025)- 2024
- [j45]Olga Dorabiala
, Aleksandr Y. Aravkin, J. Nathan Kutz:
Ensemble Principal Component Analysis. IEEE Access 12: 6663-6671 (2024) - [j44]Jacob Stevens-Haas, Yash Bhangale, J. Nathan Kutz, Aleksandr Y. Aravkin:
Learning Nonlinear Dynamics Using Kalman Smoothing. IEEE Access 12: 138564-138574 (2024) - [j43]Aleksei Sholokhov, James V. Burke, Damian F. Santomauro, Peng Zheng, Aleksandr Y. Aravkin:
A Relaxation Approach to Feature Selection for Linear Mixed Effects Models. J. Comput. Graph. Stat. 33(1): 261-275 (2024) - [j42]Aleksandr Y. Aravkin, Robert J. Baraldi, Dominique Orban:
A Levenberg-Marquardt Method for Nonsmooth Regularized Least Squares. SIAM J. Sci. Comput. 46(4): 2557- (2024) - [i31]Ariane Ducellier, Alexander Hsu, Parkes Kendrick, Bill Gustafson, Laura Dwyer-Lindgren, Christopher Murray, Peng Zheng, Aleksandr Y. Aravkin:
Uncertainty Quantification under Noisy Constraints, with Applications to Raking. CoRR abs/2407.20520 (2024) - 2023
- [j41]Aleksei Sholokhov, Peng Zheng, Aleksandr Y. Aravkin:
pysr3: A Python Package for Sparse Relaxed Regularized Regression. J. Open Source Softw. 8(86): 5155 (2023) - [i30]Aleksandr Y. Aravkin, Robert J. Baraldi, Dominique Orban:
A Levenberg-Marquardt Method for Nonsmooth Regularized Least Squares. CoRR abs/2301.02347 (2023) - [i29]Gianluigi Pillonetto, Aleksandr Y. Aravkin, Daniel Gedon, Lennart Ljung, Antônio H. Ribeiro, Thomas B. Schön:
Deep networks for system identification: a Survey. CoRR abs/2301.12832 (2023) - 2022
- [j40]Kelsey Maass, Minsun Kim, Aleksandr Y. Aravkin:
A Nonconvex Optimization Approach to IMRT Planning with Dose-Volume Constraints. INFORMS J. Comput. 34(3): 1366-1386 (2022) - [j39]Olga Dorabiala, J. Nathan Kutz, Aleksandr Y. Aravkin:
Robust trimmed k-means. Pattern Recognit. Lett. 161: 9-16 (2022) - [j38]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): 60-79 (2022) - [j37]Aleksandr Y. Aravkin, Robert J. Baraldi, Dominique Orban:
A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimization. SIAM J. Optim. 32(2): 900-929 (2022) - [i28]Olga Dorabiala, Jennifer Webster, J. Nathan Kutz, Aleksandr Y. Aravkin:
Spatiotemporal k-means. CoRR abs/2211.05337 (2022) - 2021
- [j36]Anna Scampicchio, Aleksandr Y. Aravkin, Gianluigi Pillonetto:
Stable and robust LQR design via scenario approach. Autom. 129: 109571 (2021) - [j35]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): 544-556 (2021) - [j34]Germán 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): 2087-2127 (2021) - [j33]Peng Zheng, Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin:
Estimating Shape Parameters of Piecewise Linear-Quadratic Problems. Open J. Math. Optim. 2: 1-18 (2021) - [j32]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): 2335-2358 (2021) - [j31]Tristan van Leeuwen, Aleksandr Y. Aravkin:
Variable Projection for NonSmooth Problems. SIAM J. Sci. Comput. 43(5): S249-S268 (2021) - [j30]Metin Vural, Aleksandr Y. Aravkin, Slawomir Stanczak:
$\ell _{1}$-Norm Minimization With Regula Falsi Type Root Finding Methods. IEEE Signal Process. Lett. 28: 2132-2136 (2021) - [j29]Jonathan Jonker, Peng Zheng, Aleksandr Y. Aravkin:
Efficient Robust Parameter Identification in Generalized Kalman Smoothing Models. IEEE Trans. Autom. Control. 66(10): 4852-4857 (2021) - [j28]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): 1886-1896 (2021) - [i27]Hexuan Liu, Aleksandr Y. Aravkin:
Analysis of Truncated Orthogonal Iteration for Sparse Eigenvector Problems. CoRR abs/2103.13523 (2021) - [i26]Kelsey Maass, Aleksandr Y. Aravkin, Minsun Kim:
A feasibility study of a hyperparameter tuning approach to automated inverse planning in radiotherapy. CoRR abs/2105.07024 (2021) - [i25]Olga Dorabiala, J. Nathan Kutz, Aleksandr Y. Aravkin:
Robust Trimmed k-means. CoRR abs/2108.07186 (2021) - [i24]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 abs/2110.10199 (2021) - 2020
- [j27]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: 169259-169271 (2020) - [j26]Jize Zhang, Tim Leung, Aleksandr Y. Aravkin:
Sparse mean-reverting portfolios via penalized likelihood optimization. Autom. 111 (2020) - [j25]Jize Zhang, Andrew M. Pace, Samuel A. Burden, Aleksandr Y. Aravkin:
Offline state estimation for hybrid systems via nonsmooth variable projection. Autom. 115: 108871 (2020) - [j24]Aleksandr Y. Aravkin, Damek Davis:
Trimmed Statistical Estimation via Variance Reduction. Math. Oper. Res. 45(1): 292-322 (2020) - [j23]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): 977-1002 (2020) - [i23]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 abs/2006.13380 (2020) - [i22]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 abs/2008.10740 (2020)
2010 – 2019
- 2019
- [j22]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: 1404-1423 (2019) - [j21]Jonathan Jonker, Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, Sarah E. Webster:
Fast robust methods for singular state-space models. Autom. 105: 399-405 (2019) - [j20]Aleksandr Y. Aravkin, Giulio Bottegal, Gianluigi Pillonetto:
Boosting as a kernel-based method. Mach. Learn. 108(11): 1951-1974 (2019) - [j19]Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy:
Level-set methods for convex optimization. Math. Program. 174(1-2): 359-390 (2019) - [j18]Derek Driggs, Stephen Becker, Aleksandr Y. Aravkin:
Adapting Regularized Low-Rank Models for Parallel Architectures. SIAM J. Sci. Comput. 41(1): A163-A189 (2019) - [j17]Robert J. Baraldi, Rajiv Kumar, Aleksandr Y. Aravkin:
Basis Pursuit Denoise With Nonsmooth Constraints. IEEE Trans. Signal Process. 67(22): 5811-5823 (2019) - [c31]Jize Zhang, Tim Leung, Aleksandr Y. Aravkin:
A Relaxed Optimization Approach for Cardinality-Constrained Portfolios. ECC 2019: 2885-2892 - [c30]Jihun Yun, Peng Zheng, Eunho Yang, Aurélie C. Lozano, Aleksandr Y. Aravkin:
Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning. ICML 2019: 7242-7251 - [c29]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 - [i21]Kameron Decker Harris, Aleksandr Y. Aravkin, Rajesh Rao, Bingni Wen Brunton:
Time-varying Autoregression with Low Rank Tensors. CoRR abs/1905.08389 (2019) - [i20]Aleksandr Y. Aravkin, James V. Burke, Daiwei He:
On the Global Minimizers of Real Robust Phase Retrieval with Sparse Noise. CoRR abs/1905.10358 (2019) - [i19]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 abs/1906.10612 (2019) - 2018
- [j16]Ernie Esser, Lluís Guasch, Tristan van Leeuwen, Aleksandr Y. Aravkin, Felix J. Herrmann:
Total Variation Regularization Strategies in Full-Waveform Inversion. SIAM J. Imaging Sci. 11(1): 376-406 (2018) - [j15]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): 2406-2434 (2018) - [j14]Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto:
Generalized System Identification with Stable Spline Kernels. SIAM J. Sci. Comput. 40(5): B1419-B1443 (2018) - [j13]Aleksandr Y. Aravkin, Dmitriy Drusvyatskiy, Tristan van Leeuwen:
Efficient Quadratic Penalization Through the Partial Minimization Technique. IEEE Trans. Autom. Control. 63(7): 2131-2138 (2018) - [c28]Jize Zhang, Tim Leung, Aleksandr Y. Aravkin:
Mean Reverting Portfolios via Penalized OU-Likelihood Estimation. CDC 2018: 5795-5800 - [i18]N. Benjamin Erichson, Peng Zeng, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin:
Sparse Principal Component Analysis via Variable Projection. CoRR abs/1804.00341 (2018) - [i17]Germán 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 abs/1805.09874 (2018) - [i16]Peng Zheng, Travis Askham, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin:
Sparse Relaxed Regularized Regression: SR3. CoRR abs/1807.05411 (2018) - 2017
- [j12]Aleksandr Y. Aravkin, James V. Burke, Lennart Ljung, Aurélie C. Lozano, Gianluigi Pillonetto:
Generalized Kalman smoothing: Modeling and algorithms. Autom. 86: 63-86 (2017) - [j11]Rajiv Kumar, Oscar López, 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): 264-274 (2017) - [c27]Peng Zheng, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy:
Learning Robust Representations for Computer Vision. ICCV Workshops 2017: 1784-1791 - [c26]Karthikeyan Natesan Ramamurthy, Chung-Ching Lin, Aleksandr Y. Aravkin, Sharath Pankanti, Raphael Viguier:
Distributed Bundle Adjustment. ICCV Workshops 2017: 2146-2154 - [i15]Peng Zheng, Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan:
Learning Robust Representations for Computer Vision. CoRR abs/1708.00069 (2017) - [i14]Karthikeyan Natesan Ramamurthy, Chung-Ching Lin, Aleksandr Y. Aravkin, Sharath Pankanti, Raphael Viguier:
Distributed Bundle Adjustment. CoRR abs/1708.07954 (2017) - 2016
- [j10]Giulio Bottegal, Aleksandr Y. Aravkin, Håkan Hjalmarsson, Gianluigi Pillonetto:
Robust EM kernel-based methods for linear system identification. Autom. 67: 114-126 (2016) - [j9]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) - [c25]Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan:
Beyond L2-loss functions for learning sparse models. ICASSP 2016: 4692-4696 - [c24]Aleksandr Y. Aravkin, Kush R. Varshney, Liu Yang:
Dynamic matrix factorization with social influence. MLSP 2016: 1-6 - [c23]Gianluigi Pillonetto, Aleksandr Y. Aravkin:
A stable spline convex approach to hybrid systems identification. MLSP 2016: 1-6 - [i13]Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy:
Level-set methods for convex optimization. CoRR abs/1602.01506 (2016) - [i12]Aleksandr Y. Aravkin, Stephen Becker:
Dual Smoothing and Level Set Techniques for Variational Matrix Decomposition. CoRR abs/1603.00284 (2016) - [i11]Aleksandr Y. Aravkin, Kush R. Varshney, Liu Yang:
Dynamic matrix factorization with social influence. CoRR abs/1604.06194 (2016) - [i10]Aleksandr Y. Aravkin, Damek Davis:
A SMART Stochastic Algorithm for Nonconvex Optimization with Applications to Robust Machine Learning. CoRR abs/1610.01101 (2016) - 2015
- [j8]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): 1518-1524 (2015) - [c22]Giulio Bottegal, Håkan Hjalmarsson, Aleksandr Y. Aravkin, Gianluigi Pillonetto:
Outlier robust kernel-based system identification using ℓ1-Laplace techniques. CDC 2015: 2109-2114 - [c21]Chung-Ching Lin, Sharathchandra Pankanti, Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin:
Adaptive as-natural-as-possible image stitching. CVPR 2015: 1155-1163 - [c20]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: 266-270 - 2014
- [j7]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): 217-252 (2014) - [j6]Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto:
Robust and Trend-Following Student's t Kalman Smoothers. SIAM J. Control. Optim. 52(5): 2891-2916 (2014) - [j5]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) - [c19]Omer Tripp, Salvatore Guarnieri, Marco Pistoia, Aleksandr Y. Aravkin:
ALETHEIA: Improving the Usability of Static Security Analysis. CCS 2014: 762-774 - [c18]Aleksandr Y. Aravkin, James V. Burke:
Smoothing dynamic systems with state-dependent covariance matrices. CDC 2014: 3382-3387 - [c17]Dmitry Malioutov, Aleksandr Y. Aravkin:
Iterative log thresholding. ICASSP 2014: 7198-7202 - [c16]Aleksandr Y. Aravkin, Aurélie C. Lozano, Ronny Luss, Prabhanjan Kambadur:
Orthogonal Matching Pursuit for Sparse Quantile Regression. ICDM 2014: 11-19 - [c15]Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy, Gianluigi Pillonetto:
Kalman smoothing with persistent nuisance parameters. MLSP 2014: 1-6 - [c14]Gianluigi Pillonetto, Aleksandr Y. Aravkin:
A new kernel-based approach for identification of time-varying linear systems. MLSP 2014: 1-6 - [c13]Aleksandr Y. Aravkin, Stephen Becker, Volkan Cevher, Peder A. Olsen:
A variational approach to stable principal component pursuit. UAI 2014: 32-41 - [c12]Aleksandr Y. Aravkin, Anna Choromanska, Dimitri Kanevsky, Tony Jebara:
Semistochastic Quadratic Bound Methods for Convex and Nonconvex Learning Problems. ICLR (Workshop Poster) 2014 - [i9]Aleksandr Y. Aravkin, Anju Kambadur, Aurélie C. Lozano, Ronny Luss:
Sparse Quantile Huber Regression for Efficient and Robust Estimation. CoRR abs/1402.4624 (2014) - [i8]Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan:
Beyond L2-Loss Functions for Learning Sparse Models. CoRR abs/1403.6706 (2014) - [i7]Giulio Bottegal, Aleksandr Y. Aravkin, Håkan Hjalmarsson, Gianluigi Pillonetto:
Robust EM kernel-based methods for linear system identification. CoRR abs/1411.5915 (2014) - 2013
- [j4]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): 2689-2728 (2013) - [j3]Aleksandr Y. Aravkin, James V. Burke, Michael P. Friedlander:
Variational Properties of Value Functions. SIAM J. Optim. 23(3): 1689-1717 (2013) - [c11]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: 303-308 - [c10]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: 315-320 - [c9]Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto:
Linear system identification using stable spline kernels and PLQ penalties. CDC 2013: 5168-5173 - [c8]Aleksandr Y. Aravkin, Tristan van Leeuwen, Ning Tu:
Sparse seismic imaging using variable projection. ICASSP 2013: 2065-2069 - [c7]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: 951-959 - [i6]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 abs/1301.5288 (2013) - [i5]Aleksandr Y. Aravkin, Rajiv Mittal, Hassan Mansour, Ben Recht, Felix J. Herrmann:
An SVD-free Pareto curve approach to rank minimization. CoRR abs/1302.4886 (2013) - [i4]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 abs/1309.1501 (2013) - [i3]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 abs/1309.1508 (2013) - 2012
- [j2]Aleksandr Y. Aravkin, Michael P. Friedlander, Felix J. Herrmann, Tristan van Leeuwen:
Robust inversion, dimensionality reduction, and randomized sampling. Math. Program. 134(1): 101-125 (2012) - [c6]Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto:
Nonsmooth regression and state estimation using piecewise quadratic log-concave densities. CDC 2012: 4101-4106 - [c5]Aleksandr Y. Aravkin, Xiang Li, Felix J. Herrmann:
Fast seismic imaging for marine data. ICASSP 2012: 2517-2520 - [c4]Aleksandr Y. Aravkin, Michael P. Friedlander, Tristan van Leeuwen:
Robust inversion via semistochastic dimensionality reduction. ICASSP 2012: 5245-5248 - [c3]Aleksandr Y. Aravkin, Michael Styer, Zachary Moratto, Ara V. Nefian, Michael Broxton:
Student's t robust bundle adjustment algorithm. ICIP 2012: 1757-1760 - 2011
- [j1]Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto:
An 1 -Laplace Robust Kalman Smoother. IEEE Trans. Autom. Control. 56(12): 2898-2911 (2011) - [c2]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: 156-161 - [i2]Aleksandr Y. Aravkin, Michael P. Friedlander, Tristan van Leeuwen:
Robust inversion via semistochastic dimensionality reduction. CoRR abs/1110.0895 (2011) - [i1]Aleksandr Y. Aravkin, Michael Styer, Zachary Moratto, Ara V. Nefian, Michael Broxton:
Student's T Robust Bundle Adjustment Algorithm. CoRR abs/1111.1400 (2011) - 2010
- [c1]Gianluigi Pillonetto, Aleksandr Y. Aravkin, Stefano Carpin:
The unconstrained and inequality constrained moving horizon approach to robot localization. IROS 2010: 3830-3835
Coauthor Index
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