[1] Ahmed Attia and Emil Constantinescu. “Optimal Experimental Design for Inverse Problems in the Presence of Observation Correlations“. In: arXiv preprint arXiv:2007.14476 (2020).

[2] Michel Baldin, Roger Cue, Michael Ferris, Kieran Furlong, Regi George, Mark Holzhuter, Afshin Kalantari, Carl Lipert, Doug Reinemann, Kevin Wade, Richard Wallace, Steve Wangen, Bryan Wattie, and Kent Weigel. “Creating Value from Data“. In: Hoard’s Dairy- man (2020), pp. 299 – 302.

[3] Johannes J. Brust, Roummel F. Marcia, and Cosmin G. Petra. “Computationally Efficient Decompositions of Oblique Projection Matrices“. In: SIAM Journal on Matrix Analysis and Applications 41.2 (2020), pp. 852 – 870. doi: 10.1137/19M1288115.

[4] M. Daryalal, M. Bodur, and J. Luedtke. “Lagrangian dual decision rules for multistage stochastic mixed integer programming“. Under first revision in Operations Research. 2020.

[5] Daniel Dylewsky, David Barajas-Solano, Tong Ma, Alexandre M. Tartakovsky, and J. Nathan Kutz. “Dynamic mode decomposition for forecasting and analysis of power grid load data“. In: arXiv e-prints (2020). Submitted to IEEE Transactions on Power Systems. Submitted to International Journal of Forecasting. arXiv: 2010.04248 [physics.soc-ph].

[6] Christopher J. Geoga, Mihai Anitescu, and Michael L. Stein. “Scalable Gaussian Process Computations Using Hierarchical Matrices“. In: Journal of Computational and Graphical Statistics 29.2 (2020), pp. 227 – 237. doi: 10.1080/10618600.2019.1652616. eprint: https://doi.org/10.1080/10618600.2019.1652616.

[7] C. L. Haley. “A Missing-Data Multitaper Coherence Estimator”. In: Journal of Time Series Analysis (Sept. 2020). Submitted.

[8] C. L. Haley and C. J. Geoga. “Multitaper.jl: Julia Software for Frequency-domain Analysis of Time Series“. In: Journal of Open Source Software 5.55 (2020), p. 2463.

[9] Rohit Kannan, Guzin Bayraksan, and James Luedtke. “Data-driven sample average approximation with covariate information“. Submitted. 2020.

[10] Shaohui Liu, Daniel Adrian Maldonado, and Emil M. Constantinescu. “Probabilistic analysis of masked loads with aggregated photovoltaic production“. In: Electric Power Systems Research 189 (2020), p. 106670. issn: 0378-7796. doi: https://doi.org/10.1016/j.epsr.2020.106670.

[11] N. Ho-Nguyen and S. J. Wright. “Adversarial classification via distributional robustness with Wasserstein ambiguity“. Manuscript. May 2020.

[12] M. O’Neill and S. J. Wright. “A Line-search descent algorithm for strict saddle functions with complexity guarantees“. In: arXiv preprint arXiv:2006.07925 (2020).

[13] Jangho Park and Guzin Bayraksan. “A Multistage Distributionally Robust Optimization Approach to Water Allocation under Climate Uncertainty“. Submitted. 2020. arXiv: 2005.07811 [math.OC].

[14] Jangho Park, Rebecca Stockbridge, and Guzin Bayraksan. “Variance Reduction for Sequential Sampling in Stochastic Programming“. Submitted. 2020. arXiv: 2005.02458 [math.OC].

[15] Joshua L Pulsipher and Victor M Zavala. “Measuring and optimizing system reliability: a stochastic programming approach“. In: TOP (2020), pp. 1 – 20.

[16] Vishwas Rao, Romit Maulik, Emil Constantinescu, and Mihai Anitescu. “A Machine-Learning-Based Importance Sampling Method to Compute Rare Event Probabilities“. In: Computational Science – ICCS 2020. Ed. by Valeria V. Krzhizhanovskaya, Gabor Zavodszky, Michael H. Lees, Jack J. Dongarra, Peter M. A. Sloot, Sergio Brissos, and Joao Teixeira. Cham: Springer International Publishing, 2020, pp. 169 – 182. isbn: 978-3-030-50433-5.

[17] Michael L. Stein. “A parametric model for distributions with exible behavior in both tails“. In: Environmetrics n/a.n/a (2020), e2658. doi: 10.1002/env.2658.

[18] Michael L. Stein. “Some Statistical Issues in Climate Science“. In: Statist. Sci. 35.1 (Feb. 2020), pp. 31 – 41. doi: 10.1214/19- STS730.

[19] Radoslav G. Vuchkov, Cosmin G. Petra, and Noemi Petra. “On the Derivation of Quasi-Newton Formulas for Optimization in Function Spaces“. In: Numerical Functional Analysis and Optimization 41.13 (2020), pp. 1564 – 1587. doi: 10.1080/01630563.2020.1785496.

[20] Shaobu Wang and Zhenyu Huang. “Non-equilibrium Initialization: Seamless Connection between Dynamic State Estimation and Dynamic Security Assessment”. In: Submitted to IEEE Power Engineering Letters (2020).

[21] Jiacan Yuan, Michael L. Stein, and Robert E. Kopp. “The Evolving Distribution of Relative Humidity Conditional Upon Daily Maximum Temperature in a Warming Climate“. In: Journal of Geophysical Research: Atmospheres 125.19 (2020), e2019JD032100. doi: 10.1029/2019JD032100. eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019JD032100.

[22] K. Chen, Q. Li, J. Lu, and S. J. Wright. “Randomized sampling for basis function construction in generalized nite element methods“. In: Multiscale Modeling and Simulation 18 (2020), pp. 1153 – 1177.

[23] Emil M. Constantinescu, Noemi. Petra, Julie. Bessac, and Cosmin G. Petra. “Statistical Treatment of Inverse Problems Constrained by Differential Equations-Based Models with Stochastic Terms“. In: SIAM/ASA Journal on Uncertainty Quantication 8.1 (2020), pp. 170 – 197. doi: 10.1137/18M122073X.

[24] M. C. Ferris and A. B. Philpott. “100% renewable energy with storage“. In: Energy Economics (2020). Revised, Submitted October, 2020.

[25] M. Grbuzbalaban, A. Ozdaglar, N. D. Vanli, and S. J. Wright. “Randomness and permutations in coordinate descent methods“. In: Mathematical Programming, Series B 181 (2020), pp. 349 – 376.

[26] Rohit Kannan, James R Luedtke, and Line A Roald. “Stochastic DC optimal power flow with reserve saturation“. In: Electric Power Systems Research 189 (2020), p. 106566.

[27] C. Lim, J. Linderoth, J. Luedtke, and S. J. Wright. “Parallelizing Subgradient Methods for the Lagrangian Dual in Stochastic Mixed-Integer Programming“. In: INFORMS Journal on Optimization (2020). Accepted.

[28] James Luedtke, Claudia D’Ambrosio, Je Linderoth, and Jonas Schweiger. “Strong Convex Nonlinear Relaxations of the Pooling Problem“. In: SIAM J. Optimization 30 (2020), pp. 1582 – 1609.

[29] Alejandra Pena-Ordieres, James Luedtke, and Andreas Waechter. “Solving chance-constrained problems via a smooth sample-based nonlinear approximation“. In: SIAM Journal on Optimization 30 (2020), pp. 2221-2250.

[30] S. J. Wright and C.-p. Lee. “Analyzing random permutations for cyclic coordinate descent“. In: Mathematics of Computation 89 (2020), pp. 2217-2248.

[31] Y. Xie and S. J. Wright. “Complexity of proximal augmented Lagrangian for nonconvex optimization with nonlinear equality constraints“. Technical Report arXiv:1908.00131. Revised August, 2020. University of Wisconsin-Madison, Sept. 2019.

[32] Ashley M Hou and Line A Roald. “Chance Constraint Tuning for Optimal Power Flow“. In: Probabilistic Methods Applied to Power Systems (PMAPS) (2020).

[33] Youngdae Kim and Mihai Anitescu. “A Real-Time Optimization with Warm-Start of Multiperiod AC Optimal Power Flows“. In: Electric Power Systems Research 189 (2020), p. 106721.

[34] Sen Na and Mihai Anitescu. “Exponential decay in the sensitivity analysis of nonlinear dynamic programming“. In: SIAM Journal on Optimization 30.2 (2020), pp. 1527 – 1554.

[35] Sen Na and Mihai Anitescu. “Superconvergence of Online Optimization for Model Predictive Control“. In: arXiv preprint arXiv:2001.03707 (2020).

[36] Sen Na, Sungho Shin, Mihai Anitescu, and Victor M Zavala. “Overlapping Schwarz Decomposition for Nonlinear Optimal Control“. In: arXiv preprint arXiv:2005.06674 (2020).

[37] Alejandra Pena-Ordieres, Daniel K Molzahn, Line Roald, and Andreas Waechter. “DC optimal power flow with joint chance constraints“. In: IEEE Transactions on Power Systems (2020).

[38] Sungho Shin, Mihai Anitescu, and Victor M Zavala. “Overlapping Schwarz Decomposition for Constrained Quadratic Programs“. In: arXiv preprint arXiv:2003.07502 (2020). In: 2020 59th IEEE Conference on Decision and Control (CDC). IEEE. 2020, pp. 3004-3009.

[39] K. Sundar, H. Nagarajan, S. Wang, J. Linderoth, and R. Bent. “Piecewise Polyhedral Formulations for a Multilinear Term“. In: Operations Research Letters (2020). Resubmit after minor revision.

[40] Anirudh Subramanyam, Mohamed El Tonbari, and Kibaek Kim. “Data-Driven Two-Stage Conic Optimization with Rare High-Impact Zero-One Uncertainties”. In: arXiv preprint arXiv:2001.04934 (2020). Submitted to Operations Research.

[41] Kibaek Kim and Brian Dandurand. “Scalable Branching on Dual Decomposition of Stochastic Mixed-Integer Programming Problems”. In: Mathematical Programming Computation (2020). Accepted.

[42] Tong Ma. “Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems”. In: IEEE Transactions on Neural Networks and Learning Systems (2020).

[43] Tong Ma. “Filtering adaptive output feedback control for multivariable nonlinear systems with mismatched uncertainties and unmodeled dynamics”. In: International Journal of
Robust and Nonlinear Control 30.18 (2020), pp. 8007-8028.

[44] Tong Ma. “Stochastic tracking control of multivariable nonlinear systems subject to external disturbances”. In: International Journal of Robust and Nonlinear Control 30.16
(2020), pp. 6931-6946.

[45] Tong Ma. “Filtered adaptive constrained sampled-data control for uncertain multivariable nonlinear systems”. In: International Journal of Adaptive Control and Signal Pro-
cessing 34.9 (2020), pp. 1162-1181.

[46] Shaobu Wang, Renke Huang, Zhenyu Huang, and Rui Fan. “A Robust Dynamic State Estimation Approach Against Model Errors Caused by Load Changes”. In: IEEE Transactions on Power Systems 35.6 (2020), pp. 4518-4527.

[47] Yixiang Deng, Guang Lin, and Xiu Yang. “Multifidelity data fusion via gradient-Enhanced Gaussian process regression”. In: Communications in Computational Physics 28.5 (2020), pp. 1812-1837. issn: 1991-7120.

[48] Shi Chen, Qin Li, Jianfeng Lu, and Stephen J Wright. “Manifold Learning and Nonlinear Homogenization”. In: arXiv preprint arXiv:2011.00568 (2020).