Publications

Preprints

• Uncertainty Quantification under Noisy Constraints, with Applications to Raking.
  A. Ducellier, A. Hsu, P. Kendrick, B. Gustafson, L. Dwyer-Lindgren, C. Murray, P. Zheng, A. Aravkin.

• Corrected Correlation Estimates for Meta-Analysis.
  A. Johnson-Vázquez, P. Zheng, A. Aravkin.

• Robust Nonparametric Stochastic Frontier Analysis.
  P. Zheng, N. Worku, M. Bannick, J. Dielemann, M. Weaver, C. Murray, A. Aravkin.

• Spatiotemporal k-means.
  O. Dorabiala, J. Webster, J.N. Kutz, A. Aravkin.

Articles, Proceedings and Book Chapters

2024

• Deep networks for system identification: a Survey.
  G. Pillonetto, A. Aravkin, D. Gedon, L. Ljung, A. H. Ribeiro, T.B. Schön. Automatica 171 (2025): 111907.

• Learning Nonlinear Dynamics Using Kalman Smoothing.
  J. Stevens-Haas, Y. Bhangale, A. Aravkin, N. Kutz. IEEE Access (2024).

• WENDY: Gene Regulatory Network Inference with Covariance Dynamics.
  Y. Wang, P. Zheng, Y. Cheng, Z. Wang, A. Aravkin. Math Biosci. 2024 Aug 20;377:109284.

• Sparse Independent Component Analysis with an Application to Cortical Surface fMRI Data in Autism.
  Z. Wang, I. Gaynanova, A. Aravkin, B. Risk. Journal of the American Statistical Association, (2024): 1-13.

• A Levenberg-Marquardt Method for Nonsmooth Regularized Least Squares.
  A. Aravkin, B. Baraldi, D. Orban. SIAM Journal on Scientific Computing 46.4 (2024): A2557-A2581.

• Trends and levels of the global, regional, and national burden of appendicitis between 1990 and 2021: findings from the Global Burden of Disease Study 2021.
  H. Han et al. The Lancet Gastroenterology & Hepatology, 2024.

• Global, regional, and national burden of gout, 1990–2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021.
  M. Cross et al. The Lancet Reumatology, 2024.

• Cost-effectiveness of interventions for HIV/AIDS, malaria, syphilis, and tuberculosis in 128 countries: a meta-regression analysis.
  F. Silke et al. The Lancet Global Health, 2024.

• Association Between Early Sexual Debut and New HIV Infections Among Adolescents and Young Adults in 11 African Countries.
  J. He et al. Aids and Behavoir, 2024.

• Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021.
  M. Brauer, G. Roth, A. Aravkin, P. Zheng, C. Murray, E. Gakidou et al. The Lancet, 2024.

• Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021.
  S.E. Vollset et al. The Lancet, 2024.

• A burden of proof study on alcohol consumption and ischemic heart disease.
  S. Carr et al. Nature Communications (2024).

• Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021.
  A. Ferrari et al. The Lancet (2024).

• Global, regional, and national incidence and mortality burden of non-COVID-19 lower respiratory infections and aetiologies, 1990–2021: a systematic analysis from the Global Burden of Disease Study 2021.
  R. Bender et al. The Lancet Infectious Diseases (2024).

• Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021.
  M. Naghavi et al. The Lancet (2024).

• Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021.
  J. Steinmetz et al. The Lancet Neurology 23 (4), 344-381 (2024).

• Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021.
  N. Bhattacharjee et al. The Lancet (2024).

• Global, regional, and national age-specific progress towards the 2020 milestones of the WHO End TB Strategy: a systematic analysis for the Global Burden of Disease Study 2021.
  J. Ledesma et al. The Lancet Infectious Diseases (2024).

• Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
  A. Schumacher et al. The Lancet (2024).

• Global, regional, and national burden of neck pain, 1990–2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021
  A. Wu et al. The Lancet Rheumatology 6(3), e142-e155 (2024).

• Health effects associated with chewing tobacco: a Burden of Proof study.
  G. Gil et al. Nature Communications 15 (1),1082 (2024).

• Effects of education on adult mortality: a global systematic review and meta-analysis.
  B. Mirza et al. The Lancet Public Health (2024).

• Health effects associated with exposure to secondhand smoke: a Burden of Proof study
  L. Flor et. al. Nature medicine 30.1 (2024): 149-167.

• Ensemble Principal Component Analysis.
  O. Dorabiala, A. Aravkin, J.N. Kutz. IEEE Access, January 2024.

2023

• Global Burden of Cardiovascular Diseases and Risks, 1990-2022.
  M. George et. al. Journal of the American College of Cardiology 82.25 (2023): 2350-2473.

• Health effects associated with exposure to intimate partner violence against women and childhood sexual abuse: a Burden of Proof study.
  C. Spencer et al. Nature Medicine 29, pages 3243–3258 (2023).

• Global, regional, and national burden of other musculoskeletal disorders, 1990–2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021.
  R. Black et al. M. Moberg et al. T. Gill et al. The Lancet Public Rheumatology, 5(11) E670-E682.

• Global, regional, and national mortality due to unintentional carbon monoxide poisoning, 2000–2021: results from the Global Burden of Disease Study 2021.
  R. Black et al. M. Moberg et al. The Lancet Public Health, 8(11), E839-E849.

• Global, regional, and national burden of rheumatoid arthritis, 1990–2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021.
  R. Black et al. The Lancet Rheumatology, 5(10), p. e594-e610.

• The Global, Regional, and National Burden of Adult Lip, Oral, and Pharyngeal Cancer in 204 Countries and Territories.
  A. da Cunha et al. Jama Oncology 2023, 9(10):1401-1416.

• Global, regional, and national burden of osteoarthritis, 1990–2020 and projections to 2050: a systematic analysis for the Global Burden of Disease Study 2021.
  J. Steinmetz et al., The Lancet Rheumatology 5(9), e508-e522.

• The burden of antimicrobial resistance in the Americas in 2019: a cross-country systematic analysis.
  G. Aguilar et al., The Lancet Regional Health (Americas) 2023, 25(100561).

• Global, regional, and national burden of meningitis and its aetiologies, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019.
  H. Wunrow et al., The Lancet Neurobiology (2023).

• Trends in State-Level Maternal Mortality by Racial and Ethnic Group in the United States.
  L. Feszar et al., JAMA (2023).

• Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021.
  K. Ong et al., The Lancet (2023).

• A Relaxation Approach to Feature Selection for Linear Mixed Effects Models.
  A. Sholokhov, J.V. Burke, D.F. Santomauro, P. Zheng, A. Aravkin. To appear in the Journal of Computational And Graphical Statistics (JCGS), Accepted 2023.

• Global, regional, and national prevalence and mortality burden of sickle cell disease, 2000–2021: a systematic analysis from the Global Burden of Disease Study 2021.
  A. Thompson et al., The Lancet Haematology (2023).

• Patient-specific Quality Assurance Failure Prediction with Deep Tabular Models
  R. Levin, A. Aravkin, and M. Kim. Biomedical Physics & Engineering Express. 2023 May 12;9(4).

• A Python Package for Sparse Relaxed Regularized Regression
  A. Sholokov, P. Zheng, A. Aravkin. Journal of Open Source Software (2023).

• Reply to: Concerns about the Burden of Proof studies.
  A Aravkin, S. McLaughlin, P. Zheng, H. Leschinsky, M. Brauer, S. Hay, C. Murray. Nature Medicine (2023).

• Assessing COVID-19 pandemic policies and behaviours and their economic and educational trade-offs across US states from Jan 1, 2020, to July 31, 2022: an observational analysis.
  T. Bollyky et al., The Lancet (2023).

• State-Level Cardiovascular Mortality Rates Among Hispanic, Non-Hispanic Black, and Non-Hispanic White Populations, 1990 to 2019.
  C. Johnson et al., JAMA Cardiology (2023).

• Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026.
  Micah et al., The Lancet Global Health (2023).

• Meningococcal A conjugate vaccine coverage in the meningitis belt of Africa from 2010 to 2021: A modelling study.
  Bender et al., eClinicalMedicine (2023).

2022

• Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019.
  Ikuta et al., The Lancet.

• How unhealthy is red meat? And how beneficial is it to eat vegetables? A new rating system could help you cut through the health guidelines.
  A. Aravkin, C. Razo, and J. Stanaway. Research Brief, The Conversation.

• The Burden of Proof studies: assessing the evidence of risk.
  P. Zheng, A. Aravkin, C. Murray et. al., Nature Medicine.

• Health effects associated with vegetable consumption: a Burden of Proof study
  J. Stanaway, P. Zheng, A. Aravkin, C. Murray et al., Nature Medicine.

• Health effects associated with consumption of unprocessed red meat: a Burden of Proof study
  H. Leschinsky, P. Zheng, A. Aravkin, C. Murray et al., Nature Medicine.

• Effects of elevated systolic blood pressure on ischemic heart disease: a Burden of Proof study
  C. Razo, C. Murray, G. Roth et al., Nature Medicine.

• Health effects associated with smoking: a Burden of Proof study
  X. Dai, P. Zheng, A. Aravkin, C. Murray, E. Gakidou et al., Nature Medicine.

• Estimated Global Proportions of Individuals With Persistent Fatigue, Cognitive, and Respiratory Symptom Clusters Following Symptomatic COVID-19 in 2020 and 2021.
  Wulf Hanson et. al., Journal of the American Medical Association (JAMA).

• Robust Trimmed k-means.
  O. Dorabiala, J.N. Kutz, A.Y. Aravkin. Pattern Recognition Letters.

• Life Expectancy for White, Black, and Hispanic Race/Ethnicity in U.S. States: Trends and Disparities, 1990 to 2019.
  Johnson et. al. Annals of Internal Medicine.

• Cost-effectiveness of rotavirus vaccination in children under five years of age in 195 countries: A meta-regression analysis.
  Janko et. al. Vaccine.

• Measuring the availability of human resources for health and its relationship to universal health coverage for 204 countries and territories from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019.
  Haakenstad et. al. The Lancet.

• A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimization.
  A.Y. Aravkin, R. Baraldi, D. Orban. Siam Journal of Optimization (SIOPT).

• Estimating global, regional, and national daily and cumulative infections with SARS-CoV-2 through Nov 14, 2021: a statistical analysis.
  Barber et. al. The Lancet.

• Global mortality burden attributable to non-optimal temperatures – Authors’ reply.
  Burkart et. al. The Lancet (correspondence).

• Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21
  Wang et. al. The Lancet.

• A feasibility study of a hyperparameter tuning approach to automated inverse planning in radiotherapy.
  K. Maass, A.Y. Aravkin, M. Kim. Medical Physics.

• Variation in the COVID-19 infection–fatality ratio by age, time, and geography during the pre-vaccine era: a systematic analysis
  Sorensen et al. The Lancet.

• Pandemic preparedness and COVID-19: an exploratory analysis of infection and fatality rates, and contextual factors associated with preparedness in 177 countries, from Jan 1, 2020, to Sept 30, 2021
  Bollyky et al. The Lancet.

• A nonconvex optimization approach to IMRT planning with dose-volume constraints.
  K. Maass, M. Kim, A.Y. Aravkin. Informs Journal on Computing, 2022.

• Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis
  C. Murray et al. The Lancet.

• Robust and scalable methods for the dynamic mode decomposition.
  T. Askham, P. Zheng, A.Y. Aravkin, N. Kutz. SIAM Journal on Applied Dynamical Systems (SIADS). SIAM J. Appl. Dyn. Syst., 21(1) (2022), 60–79.

2021

• Cost-effectiveness of HPV vaccination in 195 countries: A meta-regression analysis.
  K. Rosettie, J. Joffe, G. Sparks, A. Aravkin, S. Chen, K. Compton, S. Ewald, E. Mathew, D. Michael, P. Velandia, M. Miller-Petrie, L. Stafford, P. Zheng, M. Weaver, C. Murray. PLOS ONE, Published December 2021.

• Time-varying Autoregression with Low Rank Tensors.
  K. Harris, A.Y. Aravkin, R. Rao, B. Brunton. SIAM Journal on Applied Dynamical Systems (SIADS), 20(4), 2335–2358, 2021.

• l1-Norm Minimization with Regula Falsi Type Root Finding Methods.
  M. Vural, A.Y. Aravkin, S. Stan’czak. IEEE Signal Processing Letters, Vol. 28, 2021.

• Kalman smoothing and block tridiagonal systems: new connections and stability results.
  A.Y. Aravkin, J.V. Burke, B.M. Bell, G. Pillonetto. 19th IFAC Symposium on System Identification SYSID 2021. Volume 54, Issue 7, 2021, Pages 821-826.

• Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic.
  Santomauro et al. The Lancet.

• Estimating Shape Parameters of Piecewise Linear-Quadratic Problems.
  P. Zheng, K. Ramamurthy, A.Y. Aravkin. Open Journal of Mathematical Optimization (OJMO), Volume 2 (2021) , article no. 8.

• Promoting global stability in data-driven models of quadratic nonlinear dynamics.
  A.A. Kaptanoglu, J.L. Callaham, C.J. Hansen, A.Y. Aravkin, S.L. Brunton. Phys. Rev. Fluids 6, 094401.

• Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study.
  Burkart et al. The Lancet.

• A Hybrid Learning Approach to Sensor Fault Detection with Flight Test Data.
  B. de Silva, J. Callaham, J. Jonker, N. Goebel, J. Klemisch, D. McDonald, N. Hicks, J.N. Kutz, S.L. Brunton, A.Y. Aravkin. AIAA Journal, https://arc.aiaa.org/doi/10.2514/1.J059943.

• Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning. S. Brunton, J.N. Kutz, K. Manohar, A. Aravkin, K. Morgansen, J. Klemisch, N. Goebel, J. Buttrick, J. Poskin, A. Blom-Schieber, T. Hogan, D. McDonald. AIAA Journal,https://doi.org/10.2514/1.J06013.

• Estimating global and regional disruptions to routine childhood vaccine coverage during the COVID-19 pandemic in 2020: a modelling study.
  K. Causey et al. The Lancet.

• Parental education and inequalities in child mortality: a global systematic review and meta-analysis.
  M. Balaj, H. York, et al. The Lancet.

• Learning Brain Dynamics with Coupled Low-dimensional Nonlinear Oscillators and Deep Recurrent Networks.
  G. Abrevaya, G. Dumas, A.Y. Aravkin, P. Zheng, J-C. Gagnon-Audet, J. Kozloski, P. Polosecki, G. Lajoie, D. Cox, S.P. Dawson, G. Cecchi, I. Rish. Neural Computation. https://direct.mit.edu/neco/article/doi/10.1162/neco_a_01401/101867/Learning-Brain-Dynamics-with-Coupled-Low

• Estimating health care delivery system value for each US state and testing key associations.
  J. L. Dieleman et al. Estimating health care delivery system value for each US state and testing key associations. Health Sciences Research.

• Nonsmooth Variable Projection.
  T. van Leeuwen, A. Aravkin. Siam Journal of Scientific Computing (SISC), (2021): S249-S268.

• Stable and Robust LQR Design via Scenario Approach.
  A. Scampicchio, A.Y. Aravkin, G. Pillonetto. Automatica 129 (2021): 109571.

• On the Global Minimizers of Real Robust Phase Retrieval with Sparse Noise.
  D. He., J.V. Burke, and A.Y. Aravkin. in IEEE Transactions on Information Theory, vol. 67, no. 3, pp. 1886-1896, March 2021.

• Trimmed Constrained Mixed Effects Models: Formulations and Algorithms.
  P. Zheng, R. Barber, R.J.D. Sorensen, C.J.L. Murray, and A.Y. Aravkin. Journal of Computational and Graphical Statistics (JCGS), p.1-13, 2021.

2020

• Efficient Robust Parameter Identification in Generalized Kalman Smoothing Models.
  J. Jonker, P. Zheng, A.Y. Aravkin. IEEE Transactions on Automatic Control (TAC), 2020.

• Modeling COVID-19 scenarios for the United States.
  IHME Covid-19 Forecasting Team (methods contributor). Nature Medicine (2020).

• Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019.
  GBD 2019 Risk Factors Collaborators (senior author). The Lancet (2020).

• Five insights from the Global Burden of Disease Study 2019.
  GBD 2019 Viewpoint Collaborators (methods contributor & senior author on risks capstone). The Lancet (2020).

• Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019.
  GBD 2019 Demographics Collaborators (methods contributor). The Lancet (2020).

• Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019.
  GBD 2019 Diseases and Injuries Collaborators (methods contributor). The Lancet (2020).

• Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019.
  GBD 2019 Universal Health Coverage Collaborators (methods contributor). The Lancet (2020).

• Relax-and-split method for nonsmooth nonconvex problems.
  P. Zheng, A.Y. Aravkin. Inverse Problems (2020).

• A unified sparse optimization framework to learn parsimonious physics-informed models from data.
  K. Champion, P. Zheng, A.Y. Aravkin, S.L. Brunton, J.N. Kutz. IEEE Access 8 (2020): 169259-169271.

• Dimensionality Reduction and Reduced Order Modeling for Traveling Wave Physics.
  A. Mendible, S.L. Brunton, A.Y. Aravkin, W. Lowrie, J.N. Kutz. Theoretical and Computational Fluid Dynamics (2020): 1-16.

• Stable and Robust LQR Design via Scenario Approach.
  A. Scampicchio, A.Y. Aravkin, G. Pillonetto. To appear in the Proceedings of the International Federation of Automatic Control (IFAC), 2020.

• Offline state estimation for hybrid systems via nonsmooth variable projection.
  J. Zhang, A.M. Pace, S.A. Burden, A.Y. Aravkin. Automatica 115 (2020): 108871.

• Sparse Principal Component Analysis via Variable Projection.
  N.B. Erichson, P. Zheng, K. Manohar, S.L. Brunton, J.N. Kutz, A.Y. Aravkin. SIAM Journal on Applied Mathematics (2020), 80(2), 977-1002. 2020.

• Sparse Mean-Reverting Portfolios via Penalized Likelihood Optimization.
  J. Zhang, T. Leung, A.Y. Aravkin. Automatica 111 (2020): 108651.

2019

• Basis Pursuit Denoise with Nonsmooth Constraints.
  R. Baraldi, R. Kumar, A.Y. Aravkin. IEEE Transactions on Signal Processing 67.22 (2019): 5811-5823.

• Relaxation algorithms for matrix completion, with applications to seismic travel-time data interpolation.
  R. Baraldi, C. Ulberg, R. Kumar, K. Creager, A.Y. Aravkin. Inverse Problems 35 (10) (2019):105009.

• Preliminary Results in Current Profile Estimation and Doppler-aided Navigation for Autonomous Underwater Gliders.
  J. Jonker, A. Shcherbina, R. Krishfield, L. Van Uffelen, A.Y. Aravkin, S. Webster. OCEANS 2019-Marseille. IEEE, 2019.

• Robust Singular Smoothers For Tracking Using Low-Fidelity Data.
  J. Jonker, A.Y. Aravkin, J.V. Burke, G. Pillonetto, S. Webster. Proceedings of Robotics: Science and Systems, 2019. 10.15607/RSS.2019.XV.037

• Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning.
  J. Yun, P. Zheng, E. Yang, A. Lozano, A.Y. Aravkin. In International Conference on Machine Learning (ICML) (pp. 7242-7251), 2019.

• Boosting as a kernel-based method.
  A.Y. Aravkin, G. Bottegal, and G. Pillonetto. Machine Learning (2019): 1-24.

• Fast methods for robust singular state-space models.
  J. Jonker, A.Y. Aravkin, J.V. Burke, G. Pillonetto, S. Webster. Automatica, 105, 399-405, 2019.

• A Relaxed Optimization Approach for Cardinality-Constrained Portfolio Optimization.
  J. Zhang, T. Leung, A.Y. Aravkin. In 2019 18th European Control Conference (ECC) (pp. 2885-2892). IEEE, 2019.

• Trimmed Statistical Estimation via Variance Reduction.
  A.Y. Aravkin and D. Davis. Mathematics of Operations Research (MOR) (2019).

• Adapting Regularized Low Rank Models for Parallel Architectures.
  D. Driggs, S. Becker, A.Y. Aravkin. SIAM Journal on Scientific Computing (SISC) 41.1 (2019): A163-A189.

2018

• A Unified Framework for Sparse Relaxed Regularized Regression: SR3.
  P. Zheng, T. Askham, S.L. Brunton, J.N. Kutz, A.Y. Aravkin. IEEE Access, 10.1109/ACCESS.2018.2886528.

• Level-set methods for convex optimization.
  A.Y. Aravkin, J.V. Burke, D. Drusvyastkiy, M.P. Friedlander, S. Roy. Mathematical Programming, 10.1007/s10107-018-1351-8.

• Simultaneous shot inversion for nonuniform geometries using fast data interpolation,
  M. Liu, R. Kumar, E. Haber, A.Y. Aravkin. Inverse Problems, 35(2):025003, December 2018.

• Mean Reverting Portfolios via Penalized OU-Likelihood Estimation.
  J. Zhang, T. Leung, A.Y. Aravkin. Proceedings of the Conference on Decision and Control (CDC), 2018.

• Log-linear Models, Extensions, and Applications.
  Edited by A.Y. Aravkin, A. Choromanska, L. Deng, G. Heigold, T. Jebara, D. Kanevsky and S.J. Wright. MIT Press, 2018.

• High-Dimensional Trimmed Estimators: A General Framework for Robust Structured Estimation.
  E. Yang, A. Lozano, A.Y. Aravkin. Electron. J. Statist., Volume 12, Number 2 (2018), 3519-3553.

• Generalized system identification with stable spline kernels.
  A.Y. Aravkin, J.V. Burke, G. Pillonetto. SIAM Journal on Scientific Computing 40.5 (2018): B1419-B1443.

• Foundations of Gauge and Perspective Duality.
  A. Y. Aravkin, J.V. Burke, D. Drusvyatskiy, M.P. Friedlander, K. MacPhee. SIAM Journal on Optimization 28.3 (2018): 2406-2434.

• Patterns of acute bilirubin encephalopathy in Nigeria: a multicenter pre-intervention study.
  U. Diala, R. Wennberg, I. Abdulkadir Z. Farouk, C. Zabetta, E. Omoyibo A. Emokpae, A. Aravkin, B. Toma, S. Oguche, T. Slusher. Journal of Perinatology (2018).

• Total-variation regularization strategies in full-waveform inversion.
  E. Esser, L. Guasch, T. van Leeuwen, A.Y. Aravkin, F.J. Herrmann. Total Variation Regularization Strategies in Full-Waveform Inversion. SIAM Journal on Imaging Sciences, 11(1), 376-406 (2018).

2017

• Efficient quadratic penalization through the partial minimization technique.
  A.Y. Aravkin, D. Drusvyatskiy, T. van Leeuwen. IEEE Transactions of Automatic Control, 2017.

• Learning robust representations for computer vision.
  P. Zheng, A.Y. Aravkin, K. Ramamurthy, J.J. Thiagarajan. Proceedings of RCL-CV ICCV 2017.

• Distributed Bundle Adjustment.
  K. Ramamurthy, C.C. Lin, A.Y. Aravkin, S. Pankanti, R. Viguier. Proceedings of UAVision 2017/ICCV 2017.

• Generalized Kalman Smoothing: Modeling and Algorithms (Survey).
  A.Y. Aravkin, J.V. Burke, L. Ljung, A. Lozano, and G. Pillonetto. Automatica, Vol. 86, 2017, p. 63-86.

• Beating level-set methods for 3D seismic data interpolation: a primal-dual alternating approach.
  R. Kumar, O. Lopez, D. Davis, A.Y. Aravkin, F.J. Herrmann. Transactions of Computational Imaging, 3(2), p. 1-11, 2017.

2016

• Dual Smoothing and Level Set Techniques for Variational Matrix Decomposition.
  A.Y. Aravkin and S. Becker. In Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing, T. Bouwmans, N. Aybat, E. Zahzah, 2016.

• Analytics for understanding customer behavior in the energy and utility industry.
  Y. Kim, A.Y. Aravkin, H. Fei, A. Zondervan, M. Wolf. IBM Journal of Research and Development. 60(1), 11-1, 2016.

• Source estimation with surface-related multiples – fast ambiguity resolved seismic imaging.
  N. Tu, A.Y. Aravkin, T. van Leeuwen, T. Lin, F. J. Herrmann. Geophysical Journal International, 205.3(2016): 1492-1511.

• Robust EM kernel-based methods for linear system identification.
  G. Bottegal, A.Y. Aravkin, H. Hjalmarsson, G. Pillonetto. Automatica 67 (2016) 114–126.

• A stable spline convex approach to hybrid system identification.
  G. Pillonetto, A.Y. Aravkin. In Machine Learning for Signal Processing (MLSP), 2016 IEEE 26th International Workshop on.

• Dynamic matrix factorization with social influence.
  A.Y. Aravkin, K.R. Varshney, L. Yang. In Machine Learning for Signal Processing (MLSP), 2016 IEEE 26th International Workshop on.

• Beyond L2-loss functions for learning sparse models.
  K.N. Ramamurthy, A.Y. Aravkin, J. J. Thiagarajan. IEEE Conf. Acoustics, Speech, and Signal Proc. (ICASSP) (2016) p. 4692-4696.

2015

• Efficient matrix completion for seismic data reconstruction.
  R. Kumar, C. Da Silva, O. Akalin, A.Y. Aravkin, H. Mansour, B. Recht, F.J. Herrmann. Geophysics 80, no. 5 (2015): V97-V114.

• Adaptive as-natural-as-possible image stitching.
  C-C. Lin, S.U. Pankanti, K.N. Ramamurthy, and A.Y. Aravkin. In Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on, p. 1155–1163, 2015.

• Outlier Robust Kernel-Based System Identification Using L1-Laplace Techniques.
  G. Bottegal, H. Hjalmarsson, A.Y. Aravkin, G. Pillonetto, In Proceedings of IEEE Conf. Decision and Control (CDC) (2015), p. 2109-2114.

• General Optimization Framework for Robust and Regularized 3D Full Waveform Inversion.
  S. Becker, L. Horesh, A.Y. Aravkin, S. Zhuk. In EAGE Technical Program Expanded Abstracts, 2015.

• Automatic salt delineation — Wavefield Reconstruction Inversion with convex constraints.
  E. Esser, L. Guasch, T. van Leeuwen, A.Y. Aravkin, and F.J. Herrmann. In SEG Technical Program Expanded Abstracts, 2015.

• Source estimation for wave equation with uncertain parameters.
  S. Zhuk, S. Moore, A. Nogueira, A. Rawlinson, T. Tchrakian, L. Horesh, A. Aravkin and A. Akhriev. In Control Conference (ECC) 2015 European, p. 266-270.

2014

• Optimization viewpoint on Kalman smoothing, with applications to robust and sparse estimation.
  A.Y. Aravkin, J.V. Burke, and G. Pillonetto. In Compressed Sensing and Sparse Filtering, A.Y. Carmi, L.S. Mihaylova, S.J. Godsill Eds., Signals and Communications Technology, Springer, p. 237-281, 2014.

• Statistical analysis of national and Washington State fish consumption data.
  N. L. Polissar, M. Neradilek, D. S. Hippe, A. Y. Aravkin, P. Danaher, J. Kalat, peer reviewed technical report for Washington State Department of Ecology, 2014.

• Serum bilirubin and bilirubin/albumin ratio as predictors of bilirubin encephalopathy.
  I. Iskander, R. Gamaleldin, S. El Houchi, A. El Shenawy, I. Seoud, N. El Gharbawi, H. Abou-Youssef, A. Aravkin, and R. Wennberg, Pediatrics, DOI: 10.1542/peds.2013-1764, 2014.

• Orthogonal matching pursuit for sparse quantile regression.
  A.Y. Aravkin, A. Kambadur, A.C. Lozano, and R. Luss. In Data Mining (ICDM), 2014 IEEE International Conference, pp. 11-19.

• Fast methods for denoising matrix completion formulations, with applications to robust seismic data interpolation.
  A.Y. Aravkin, R. Kumar, H. Mansour, B. Recht, and F.J. Herrmann. SIAM J. Sci. Comput., 36(5) (2014), S237–S266.

• Robust and trend following Student’s t Kalman smoothers.
  A.Y. Aravkin, J.V. Burke, G. Pillonetto. SIAM J. Control Optim. 52-5 (2014), pp. 2891-2916.

• A variational approach to stable principal component pursuit.
  A.Y. Aravkin, S. Becker, V. Cevher, and P. Olsen. In 30th Conference on Uncertainty in Artificial Intelligence (UAI), no. EPFL-CONF-199542. 2014.

• The connection between Bayesian estimation of a Gaussian random field and RKHS.
  A.Y. Aravkin, B.M. Bell, J.V. Burke, and G. Pillonetto. IEEE Transactions on Neural Networks and Learning Systems, PP(99), 2014.

• Convex vs. nonconvex approaches for sparse estimation: the mean squared properties of ARD and GLasso.
  A.Y. Aravkin, J.V. Burke, A. Chiuso, and G. Pillonetto. Journal of Machine Learning Research (JMLR), Volume 15, 217-252, 2014.

• Source separation via SVD-free rank minimization in the hierarchical semi-separable representation.
  H. Wason, R. Kumar, A.Y. Aravkin, and F. J. Herrmann. SEG Annual Meeting of the Society of Exploration Geophysicists, 2014.

• Aletheia: improving the usability of static security analysis.
  O. Tripp, S. Guarnieri, M. Pistoia and A. Aravkin. Proceedings of the 2014 ACM SIGSAC on Computer and Communications Security, 762-774.

• Kalman smoothing with persistent nuisance parameters.
  A.Y. Aravkin, K.N. Ramamurthy, and G. Pillonetto. Machine Learning for Signal Processing (MLSP), IEEE International Workshop on, 2014.

• A new kernel-based approach for identification of time-varying linear systems.
  G. Pillonetto and A.Y. Aravkin. Machine Learning for Signal Processing (MLSP), IEEE International Workshop on, 2014.

• Smoothing dynamic systems with state-dependent covariance matrices.
  A.Y. Aravkin and J.V. Burke. Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on, 3382-3387.

• Semistochastic quadratic bound methods.
  A.Y. Aravkin, A. Choromanska, T. Jebara and D. Kanevsky. International Conference on Learning Representations (ICLR) Workshop, 2014.

• SVD-free low-rank matrix factorization : wavefield reconstruction via jittered subsampling and reciprocity.
  R. Kumar, A.Y. Aravkin, E. Esser, H. Mansour and F.J. Herrmann. 6th EAGE Conference and Exhibition 2014.

• Outlier robust system identification: a Bayesian kernel-based approach.
  G. Bottegal, A.Y. Aravkin, H. Hjalmarsson and G. Pillonetto. IFAC Proceedings Volumes 47.3 (2014): 1073-1078.

• Iterative log-thresholding.
  D. Malioutov and A.Y. Aravkin. In Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on, pp. 7198-7202.

2013

• Fast dual variational inference for non-conjugate latent Gaussian models.
  E. Khan, A.Y. Aravkin, M.P. Friedlander, and M. Seeger.
  JMLR W&CP 28(3):951-959, 2013.

• Sparse/robust estimation and Kalman smoothing with nonsmooth log-concave densities: modeling, computation, and theory.
  A.Y. Aravkin, J.V. Burke, and G. Pillonetto. Journal of Machine Learning Research (JMLR) (3), 2689-2728, September 2013.

• Variational properties of value functions.
  A.Y. Aravkin, J.V. Burke, M.P. Friedlander. SIAM Journal of Optimization (SIOPT), Vol. 23, No. 3, pp. 1689–1717, August 2013.

• Accelerating Hessian-free optimization for deep neural networks by implicit preconditioning and sampling.
  T.N. Sainath, L. Horesh, B. Kingsbury, A.Y. Aravkin, B. Ramabhadran. In Automatic Speech Recognition and Understanding (ASRU), 2013 IEEE Workshop on (pp. 303-308).

• Improvements for deep convolutional neural networks for LVCSR.
  T.N. Sainath, B. Kingsbury, A. Mohamed, G.E. Dahl, G. Saon, H. Soltau, T. Beran, A.Y. Aravkin, B. Ramabhadran. In Automatic Speech Recognition and Understanding (ASRU), 2013 IEEE Workshop on (pp. 315-320).

• Linear system identification using stable spline kernels and PLQ penalties.
  A.Y. Aravkin, J.V. Burke and G. Pillonetto.
  In Decision and Control (CDC), 2013 IEEE 52nd annual conference on (pp. 5168-5173).

• Reconstruction of seismic wavefields via low-rank matrix factorization in the HSS matrix representation.
  R. Kumar, H. Mansour, A.Y. Aravkin, and F.J. Herrmann. 2013 SEG Annual Meeting. Society of Exploration Geophysicists, 2013.

• Sparse seismic imaging using variable projection.
  A.Y. Aravkin, T. van Leeuwen and N. Tu. In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on (pp. 2065-2069).

• In which domain should we measure the misfit for robust full waveform inversion?
  T. van Leeuwen, A.Y. Aravkin, H. Calandra and F.J. Herrmann. 75th EAGE Conference & Exhibition incorporating SPE EUROPEC 2013.

• Fast least-squares RTM with source wavelet estimation using multiples.
  N. Tu, A.Y. Aravkin, T. van Leeuwen, and F.J. Herrmann. 75th EAGE Conference & Exhibition incorporating SPE EUROPEC 2013.

• Seismic data interpolation and de-noising using robust matrix factorization.
  R. Kumar, A.Y. Aravkin, H. Mansour, B. Recht, F.J. Herrmann. 75th EAGE Conference & Exhibition incorporating SPE EUROPEC 2013.

• (18)F-FDG PET/CT-positive internal mammary lymph nodes: pathologic correlation by ultrasound-guided fine-needle aspiration and assessment of associated risk factors.
  C.L. Wang, M.J. Eissa, J.V. Rogers, A.Y. Aravkin, B.A. Porter, J.D. Beatty. AJR Am J Roentgenol. 2013 May; 200(5): 1138-44.

2012

• Estimating nuisance parameters in inverse problems.
  A.Y. Aravkin and T. van Leeuwen. Inverse Problems, 28(11):115016, October 2012.

• Robust inversion, dimensionality reduction, and randomized sampling.
  A.Y. Aravkin, M.P. Friedlander, F.J. Herrmann, and T. van Leeuwen. Mathematical Programming, 134(1):101-125, 2012.

• Fast randomized full waveform inversion with compressive sensing.
  X. Li, A.Y. Aravkin, T. van Leeuwen,and F.J. Herrmann. Geophysics 77(3), A13-A17, 2012.

• Nonsmooth regression and state estimation using piecewise quadratic log-concave densities.
  A.Y. Aravkin, J.V. Burke and G. Pillonetto. In Decision and Control (CDC), 2012 IEEE 51st Annual Conference on (pp. 4101-4106).

• On non-uniqueness of the Student’s t formulation for linear inverse problems.
  A.Y. Aravkin, T. van Leeuwen, K. Bube and F.J. Herrmann. 2012 SEG Annual Meeting. Society of Exploration Geophysicists.

• Student’s t robust bundle adjustment algorithm.
  A.Y. Aravkin, M. Styer, Z. Moratto, A. Nefian, and M. Broxton. In Image Processing (ICIP), 2012 19th IEEE International Conference on (pp. 1757-1760).

• Robust and trend following Kalman smoothers using Student’s t.
  A.Y. Aravkin, J.V. Burke, and G. Pillonetto. IFAC Proceedings Volumes, 45(16), 1215-1220.

• A statistical and computational theory for robust and sparse Kalman smoothing.
  A.Y. Aravkin, J.V. Burke, and G. Pillonetto. IFAC Proceedings Volumes, 45(16), 894-899.

• On the estimation of hyperparameters for empirical Bayes estimators: MML vs. minimum MSE.
  A.Y. Aravkin, J.V. Burke, A. Chiuso, and G. Pillonetto. IFAC Proceedings Volumes, 45(16), 125-130.

• On the MSE properties of empirical Bayes methods for sparse estimation.
  A.Y. Aravkin, J.V. Burke, A. Chiuso, and G. Pillonetto. IFAC Proceedings Volumes, 45(16), 965-970.

• Source estimation for frequency-domain FWI with robust penalties.
  A.Y. Aravkin, T. van Leeuwen, H. Calandra and F.J. Herrmann. In 74th EAGE Conference and Exhibition incorporating EUROPEC 2012.

• Robust inversion via semistochastic dimensionality reduction.
  A.Y. Aravkin, M.P. Friedlander, and T. van Leeuwen. IEEE Conf. Acoustics, Speech, and Signal Proc. (ICASSP), 2012.

• Fast seismic imaging for marine data.
  A.Y. Aravkin, X. Li and F.J. Herrmann. IEEE Conf. Acoustics, Speech, and Signal Proc. (ICASSP), 2012.

• Full-waveform inversion with randomized L1 recovery for the model updates.
  X. Li, A.Y. Aravkin, T. van Leeuwen, and F.J. Herrmann. In 73rd EAGE Conference and Exhibition incorporating SPE EUROPEC 2011.

• A nonlinear sparsity promoting formulation and algorithm for full waveform inversion.
  A.Y. Aravkin, T. van Leeuwen, J.V. Burke and F.J. Herrmann. In 73rd EAGE Conference and Exhibition incorporating SPE EUROPEC 2011.

2011

• Risk factors of neurotoxicity in newborns with severe neonatal hyperbilirubinemia.
  R. Gammeldin, I. Iskander, I. Seoud, H. Aboraya, A. Aravkin, P. Sampson, R. Wennberg, Pediatrics 128(4), 2011, e925-e931.

• Seismic waveform inversion by stochastic optimization.
  T. van Leeuwen, A.Y. Aravkin, and F.J. Herrmann. International Journal of Geophysics, vol. 2011, Article ID 689041, 2011.

• An l1-Laplace robust Kalman smoother.
  A.Y. Aravkin, B.M. Bell, J.V. Burke, G. Pillonetto. IEEE Transactions of Automatic Control (TAC), 56(12):2898-2911, 2011.

• Convex vs. nonconvex approaches for sparse estimation: lasso, MKL, and hyperparameter lasso.
  A.Y. Aravkin, J.V. Burke, A. Chiuso and G. Pillonetto. Proceedings of IEEE Conf. Decision and Control (CDC), 50th conference on, 2011, 156-161.

• A modified, sparsity promoting Gauss-Newton algorithm for seismic waveform inversion.
  F.J. Herrmann, X. Li, A.Y. Aravkin, and T. van Leeuwen. Proceedings of the International Society of Optics and Photonics (SPIE), 8138, 8130V, 2011.

• Learning using state space kernel machines.
  A.Y. Aravkin, B.M. Bell, J.V. Burke, and G. Pillonetto. IFAC Proceedings Volumes, 44(1), 2296-2302.

• Robust full waveform inversion using Student’s t distribution.
  A.Y. Aravkin, T. van Leeuwen, and F.J. Herrmann. Proceedings of the Society of Exploration Geophysicists (SEG), 2011.

• Positron emission mammography: correlation of estrogen receptor, progresterone receptor, and human epidermal growth factor receptor 2 status and 18F-FDG.
  C. Wang, L. MacDonald, J. Rogers, A. Aravkin, D. Haseley, J. Beatty. AJR Am J Roentgenol. 2011 Aug; 197(2): W247-55.

2010

• Robust methods for Kalman filtering/smoothing and bundle adjustment.
  A.Y. Aravkin, Ph.D. Thesis, University of Washington, 2010.

• The unconstrained and inequality constrained moving horizon approach to robot localization.
  G. Pillonetto, A.Y. Aravkin, and S. Carpin. In Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on (pp. 3830-3835)

2009

• Intervention guidelines for neonatal hyperbilirubinemia: an evidence based quagmire.
  R. Wennberg, C. Ahlfors and A. Aravkin, Curr. Pharm. Design 2009; 15(25):2939-45.

Technical Reports

• Analysis of Relaxation Methods to Feature Selection for Mixed Effects Models.
  A. Sholokhov, J.V. Burke, P. Zheng, A. Aravkin.

• Theoretical Advances in Current Estimation and Navigation from a Glider-Based Acoustic Doppler Current Profiler (ADCP).
  J. Stevens-Haas, S. Webster, A.Y. Aravkin.

• A Proof of Principle: Multi-Modality Radiotherapy Optimization.
  R. Levin, A.Y. Aravkin, M. Kim.

• Analysis of Truncated Orthogonal Iteration for Sparse Eigenvector Problems.
  H. Liu, A.Y. Aravkin.

• Analysis and Methods to Mitigate Effects of Under-reporting in Count Data.
  J. Brennan, M. Bannick, N. Kassebaum, L. Wilner, A. Thomson, A.Y. Aravkin, P. Zheng.

• Global projections of lives saved from COVID-19 with universal mask use.
  IHME Covid-19 Forecasting Team.

• IRLS for Sparse Recovery Revisited: Examples of Failure and a Remedy.
  A.Y. Aravkin, J.V. Burke, and D. He.

• Forecasting the impact of the first wave of the COVID-19 pandemic on hospital demand and deaths for the USA and European Economic Area countries, posted on Medrxiv. IHME COVID-19 health service utilization forecasting team.

• Computer Assisted Localization of a Heart Arrhythmia.
  C. Vogl, P. Zheng, S. Seslar, A.Y. Aravkin.

• Fast and simple comparison of semi-structured data, with emphasis on electronic health records.
  M. Robinson, J. Hadlock, J. Yu, A. Khatamian, A.Y. Aravkin, E. Deutsch, N. Price, S. Huang, G.Glusman.

• Generalized Linear Model for Gamma Distributed Variables via Elastic Net Regularization.
  X. Chen, A.Y. Aravkin, and D. Martin.

• Time series using exponential smoothing cells.
  A. Abrami, A.Y. Aravkin, Y. Kim.

• Automatic Inference of the Quantile Parameter.
  K.N. Ramamurthy, A.Y. Aravkin, J.J. Thiagarajan. arXiv preprint arXiv:1511.03990 (2015).