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[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] A. Bohm and S. J. Wright. “Variable smoothing for weak convex composite functions“. Technical Report. In review. Mar. 2020.

[4] Johannes J. Brust, Sven Leyer, and Cosmin G. Petra. “Compact Representations of Structured BFGS Matrices“. In: Journal of Computational Optimization and Applications (submitted, 2020).

[5] 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.

[6] F. E. Curtis, D. P. Robinson, C. W. Royer, and S. J. Wright. “Trust-region Newton-CG with strong second-order complexity guarantees for nonconvex optimization“. In: arXiv preprint arXiv:1912.04365 arXiv:1912.04365 (2019). Revised July 2020.

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

[8] 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. arXiv: 2010.04248 [physics.soc-ph].

[9] Christopher J Geoga, Mihai Anitescu, and Michael L Stein. “Flexible nonstationary spatio-temporal modeling of high-frequency monitoring data“. In: arXiv preprint arXiv:2007.11418 (2020).

[10] 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.

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

[14] 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.

[15] Tong Ma, David A. Barajas-Solano, Ramakrishna Tipireddy, and Alexandre M. Tartakovsky. “Physics-Informed Gaussian Process Regression for Probabilistic States Estimation and Forecasting in Power Grids“. In: arXiv e-prints, http://arxiv.org/abs/2010.04591 (Oct. 2020).

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

[17] 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).

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

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

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

[21] 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.

[22] 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.

[23] Michael L. Stein. “Parametric models for distributions when interest is in extremes with an application to daily temperature“. In: Extremes n/a.n/a (2020), n/a. doi: https://doi.org/10.1007/s10687-020-00378-z.

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[26] Peng Wang, Shaobu Wang, Renke Huang, and Zhenyu Huang. “Quantifying bounds of model gap for synchronous generators”. In: Submitted to IEEE Transactions on Power Systems (2020).

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[28] 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.

[29] 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.

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[33] 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.

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[37] 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.

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[39] M. O’Neill and S. J. Wright. “A log-barrier Newton-CG method for bound constrained optimization with complexity guarantees“. In: IMA Journal of Numerical Analysis (2020).

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[41] Alberto Del Pia, Dion Gijswijt, Je Linderoth, and Haoran Zhu. “Integer Packing Sets Form a Well-Quasi Ordering“. In: Operations Research Letters (2020). Submitted. 2020.

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[46] 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.

[47] Amanda Lenzi, Julie Bessac, and Mihai Anitescu. “Power Grid Frequency Prediction Using Spatio-Temporal Modeling”. Submitted to Journal of Statistical Analysis and Data Mining.

[48] 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.

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

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

[51] 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).

[52] Vishwas Rao and Mihai Anitescu. “Efficient computation of extreme excursion probabilities for dynamical systems“. In: arXiv preprint arXiv:2001.11904 (2020).

[53] Noah Rhodes, David Fobes, Carleton Coffrin, and Line Roald. “PowerModelsRestoration. jl: An Open-Source Framework for Exploring Power Network Restoration Algorithms“. In: Power Systems Computation Conference (PSCC) (2020).

[54] Noah Rhodes, Lewis Ntaimo, and Line Roald. “Balancing Wildfire Risk and Power Outages through Optimized Power Shut-Offs“. In: under revision (2020).

[55] Sungho Shin, Mihai Anitescu, and Victor M Zavala. “Overlapping Schwarz Decomposition for Constrained Quadratic Programs“. In: arXiv preprint arXiv:2003.07502 (2020).

[56] 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.

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

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

[60] Tong Ma. “Filtering adaptive output feedback control for multivariable nonlinear systems with mismatched uncertainties and unmodeled dynamics”. In: International Journal of
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[61] Tong Ma. “Stochastic tracking control of multivariable nonlinear systems subject to external disturbances”. In: International Journal of Robust and Nonlinear Control 30.16
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[62] Tong Ma. “Filtered adaptive constrained sampled-data control for uncertain multivariable nonlinear systems”. In: International Journal of Adaptive Control and Signal Pro-
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[63] 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.

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