2018

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1) Samuel Baugh and Michael L Stein. “Computationally efficient spatial modeling using recursive skeletonization factorizations”. In: Spatial Statistics 27 (2018), pp. 18–30.
2) El Houcine Bergou, Youssef Diouane, Vyacheslav Kungurtsev, and Cl ́ement W. Royer.
A stochastic Levenberg-Marquardt method using random models with application to data assimilation. Submitted, arXiv:1807.02176. 2018.
3) El Houcine Bergou, Youssef Diouane, Vyacheslav Kungurtsev, and Cl ́ement W. Royer. A subsampling line-search method with second-order results. Submitted, arXiv:1810.07211. 2018.
4) Merve Bodur and James Luedtke. “Two-stage linear decision rules for multi-stage stochas- tic programming”. In: Mathematical Programming, Series B (2018). doi: 10.1007/ s10107-018-1339-4.
5) N. Boland, J. Christiansen, B. Dandurand, A. Eberhard, J. Linderoth, J. Luedtke, and F. Oliveira. “Combining Progressive Hedging with a Frank-Wolfe Method to Compute Lagrangian Dual Bounds in Stochastic Mixed-Integer Programming”. In: SIAM Journal on Optimization 28.2 (2018), pp. 1312–1336.
6) P. Bonami, O. Gunluk, and J. Linderoth. “Globally Solving Nonconvex Quadratic Pro- gramming Problems with Box Constraints via Integer Programming Methods”. In: Math- ematical Programming Computation 10.3 (2018), pp. 333–382.
7) K. Chen, Q. Li, J. Lu, and S. J. Wright. Random sampling and efficient algorithms for multiscale PDEs. Technical Report arXiv:1807.08848. University of Wisconsin-Madison, 2018.
8) E.M. Constantinescu, N. Petra, J. Bessac, and C.G. Petra. “Statistical treatment of in- verse problems constrained by differential equations-based models with stochastic terms”. In: SIAM/ASA Journal on Uncertainty Quantification, Submitted (2018). url: https: //arxiv.org/abs/1810.08557.
9) H. Dong, K. Chen, and J. Linderoth. Regularization vs. Relaxation: A Convexifica- tion Perspective of Statistical Variable Selection. Submitted. 2018. url: http://www. optimization-online.org/DB%5C_HTML/2015/05/4932.html.
10) M. C. Ferris, O. Huber, and Y. Kim. “Solving stochastic equilibria: EMP, Selkie, and optimal value functions”. In: Oberwolfach Reports 38 (2018). doi: 10.4171/OWR/2018/ 38.
11) Christopher J Geoga, Charlotte L Haley, Andrew R Siegel, and Mihai Anitescu. “Frequency– wavenumber spectral analysis of spatio-temporal flows”. In: Journal of Fluid Mechanics 848 (2018), pp. 545–559.
12) M. Habibian, G. Zakeri, A. Downward, M. F. Anjos, and M. Ferris. “Co-optimization of demand response and interruptible load reserve offers for a price-making major con- sumer”. In: Energy Systems (Nov. 2018), p. 127.
13) M. Hamzeei and J. Luedtke. “Service network design with equilibrium-driven demands”. In: IISE Transactions 50 (2018), pp. 959–969.
14) B. Hu, S. J. Wright, and L. Lessard. “Dissipativity Theory for Accelerating Stochas- tic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs”. In: Proceedings of the 35th International Conference on Machine Learning, ICML 2018. Stockholm, 2018, pp. 2043–2052.
15) Kibaek Kim, Mihai Anitescu, and Victor M Zavala. “An Asynchronous Decomposition Algorithm for Security Constrained Unit Commitment Under Contingency Events”. In: 2018 Power Systems Computation Conference (PSCC). IEEE. 2018, pp. 1–8.
16) Kibaek Kim, Audun Botterud, and Feng Qiu. “Temporal decomposition for improved unit commitment in power system production cost modeling”. In: IEEE Transactions on Power Systems 33.5 (2018), pp. 5276–5287.
17) Kibaek Kim and Brian Dandurand. “Scalable Branching on Dual Decomposition of Stochastic Mixed-Integer Programming Problems”. In: Mathematical Programming Com- putation (under review) (2018).
18) C.-p. Lee, C. H. Lim, and S. J. Wright. “A distributed quasi-Newton algorithm for empirical risk minimization with nonsmooth regularization”. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. ACM, 2018, pp. 1646–1655.
19) C.-p. Lee and S. J. Wright. “Random permutations fix a worst case for cyclic coordinate descent”. In: IMA Journal of Numerical Analysis 39 (July 2018). To appear in IMA Journal on Numerical Analysis, pp. 1246–1275.
20) C. Lim, J. Linderoth, J. Luedtke, and S. J. Wright. Parallelizing Subgradient Methods for the Lagrangian Dual in Stochastic Mixed-Integer Programming. submitted to INFORMS Journal on Optimization. 2018.
21) James Luedtke, Claudia D’Ambrosio, Jeff Linderoth, and Jonas Schweiger. Strong Convex Nonlinear Relaxations of the Pooling Problem. submitted to SIAM J. Optimization. 2018. url: arXiv:1803.02955.
22) D. A. Maldonado, M. Schanen, and M. Anitescu. “Uncertainty Propagation in Power System Dynamics with the Method of Moments”. In: 2018 IEEE Power Energy Society General Meeting (PESGM). Aug. 2018, pp. 1–5. doi: 10.1109/PESGM.2018.8586023
23) Michael O’Neill and Stephen J. Wright. “Behavior of accelerated gradient methods near critical points of nonconvex problems”. In: Mathematical Programming, Series B (2018)
24) B. Park, M. C. Ferris, and C. L. DeMarco. “Sparse tableau approach for power system analysis and design”. In: North American Power Symposium (NAPS), IEEE (2018). doi: 10.1109/NAPS.2018.8600643.
25) C. G. Petra, F. Qiang, M. Lubin, and J. Huchette. “On efficient Hessian computation using the edge pushing algorithm in Julia”. In: Optimization Methods and Software 33.4-6 (2018), pp. 1010–1029. doi: 10.1080/10556788.2018.1480625.
26) Cosmin G. Petra. “A memory-distributed quasi-Newton solver for nonlinear program- ming problems with a small number of general constraints”. In: Journal of Parallel and Distributed Computing 133 (2019), pp. 337–348. issn: 0743-7315. doi: https://doi. org/10.1016/j.jpdc.2018.10.009.
27) Jacob Price and Panos Stinis. Renormalization and blow-up for the 3D Euler equations. arXiv:1805.08766. 2018.
28) J. Pulsipher and V.M. Zavala. “A Mixed-Integer Conic Programming Formulation for Computation of the Flexibility Index under Multivariate Gaussian Uncertainty”. In: Computers & Chemical Engineering 119.2 (2018), pp. 302–308.
29) Cl´ement W. Royer and Stephen J. Wright. “Complexity analysis of second-order line- search algorithms for smooth nonconvex optimization”. In: SIAM Journal on Optimiza- tion 28.2 (2018), pp. 1448–1477. doi: 10.1137/17M1134329
30) M. Schanen, F. Gilbert, C. G. Petra, and M. Anitescu. “Toward Multiperiod AC-Based Contingency Constrained Optimal Power Flow at Large Scale”. In: 2018 Power Systems Computation Conference (PSCC). June 2018, pp. 1–7
31) Wanting Xu and Mihai Anitescu. “Exponentially accurate temporal decomposition for long-horizon linear-quadratic dynamic optimization”. In: SIAM Journal on Optimization 28.3 (2018), pp. 2541–2573.
32) X. Zhang, X. Zhu, and S. J. Wright. “Training Set Debugging Using Trusted Items”. In AAAI Conference on Artificial Intelligence. AAAI, 2018.
33) Junbo Zhao, Shaobu Wang, Lamine Mili, Brett Amidan, Renke Huang, and Zhenyu Huang. “A Robust State Estimation Framework Considering Measurement Correlations and Imperfect Synchronization”. In: IEEE Transactions on Power Systems 33.4 (July 2018), pp. 4604–4613.