Beiträge zu Sammelwerken 2021

  • D. Dvinskikh, D. Tiapkin, Improved complexity bounds in Wasserstein barycenter problem, in: 24th International Conference on Artificial Intelligence and Statistics (AISTATS), A. Banerjee, K. Fukumizu, eds., 130 of Proceedings of Machine Learning Research, Microtome Publishing, Brookline, MA, USA, 2021, pp. 1738--1746.
  • A. Agafonov, P. Dvurechensky, G. Scutari, A. Gasnikov, D. Kamzolov, A. Lukashevich, A. Daneshmand, An accelerated second-order method for distributed stochastic optimization, in: 60th IEEE Conference on Decision and Control (CDC), IEEE, 2021, pp. 2407--2413, DOI 10.1109/CDC45484.2021.9683400 .
  • A. Daneshmand, G. Scutari, P. Dvurechensky, A. Gasnikov, Newton method over networks is fast up to the statistical precision, in: Proceedings of the 38th International Conference on Machine Learning, 139 of Proceedings of Machine Learning Research, 2021, pp. 2398--2409.
  • E. Gladin, A. Sadiev, A. Gasnikov, P. Dvurechensky, A. Beznosikov, M. Alkousa, Solving smooth min-min and min-max problems by mixed oracle algorithms, in: Mathematical Optimization Theory and Operations Research: Recent Trends, A. Strekalovsky, Y. Kochetov, T. Gruzdeva, A. Orlov , eds., 1476 of Communications in Computer and Information Science book series (CCIS), Springer International Publishing, Basel, 2021, pp. 19--40, DOI 10.1007/978-3-030-86433-0_2 .
  • S. Guminov, P. Dvurechensky, N. Tupitsa, A. Gasnikov, On a combination of alternating minimization and Nesterov's momentum, in: Proceedings of the 38th International Conference on Machine Learning, 139 of Proceedings of Machine Learning Research, 2021, pp. 3886--3898.
  • D. Pasechnyuk, P. Dvurechensky, S. Omelchenko, A. Gasnikov, Stochastic optimization for dynamic pricing, in: Advances in Optimization and Applications, N.N. Olenev, Y.G. Evtushenko, M. Jaćimović, M. Khachay, eds., 1514 of Communications in Computer and Information Science, Springer Nature Switzerland AG, Cham, 2021, pp. 82--94, DOI 10.1007/978-3-030-92711-0 .
  • A. Rogozin, M. Bochko, P. Dvurechensky, A. Gasnikov, V. Lukoshkin, An accelerated method for decentralized distributed stochastic optimization over time-varying graphs, in: 2021 IEEE 60th Annual Conference on Decision and Control (CDC), IEEE, 2021, pp. 3367--3373, DOI 10.1109/CDC45484.2021.9683400 .
  • A. Sadiev , A. Beznosikov, P. Dvurechensky, A. Gasnikov, Zeroth-order algorithms for smooth saddle-point problems, in: Mathematical Optimization Theory and Operations Research: Recent Trends, A. Strekalovsky, Y. Kochetov, T. Gruzdeva, A. Orlov , eds., 1476 of Communications in Computer and Information Science book series (CCIS), Springer International Publishing, Basel, 2021, pp. 71--85, DOI 10.1007/978-3-030-86433-0_5 .
  • K. Safin, P. Dvurechensky, A. Gasnikov, Adaptive gradient-free method for stochastic optimization, in: Advances in Optimization and Applications, N.N. Olenev, Y.G. Evtushenko, M. Jaćimović, M. Khachay, eds., 1514 of Communications in Computer and Information Science, Springer Nature Switzerland AG, Cham, 2021, pp. 95--108, DOI 10.1007/978-3-030-92711-0_7 .
  • S. Schulz, M. O'Donovan, D. Chaudhuri, S.K. Patra, P. Farrell, O. Marquardt, T. Streckenbach, Th. Koprucki, Connecting atomistic and continuum models for (In,Ga)N quantum wells: From tight-binding energy landscapes to electronic structure and carrier transport, in: 2021 International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD), IEEE Conference Publications Management Group, 2021, pp. 135--136, DOI 10.1109/NUSOD52207.2021.9541461 .
  • K. Hopf, Global existence analysis of energy-reaction-diffusion systems, in: Report 29: Variational Methods for Evolution (hybrid meeting), A. Mielke, M. Peletier, D. Slepcev, eds., 17 of Oberwolfach Reports, European Mathematical Society Publishing House, Zurich, 2021, pp. 1418--1421, DOI 10.4171/OWR/2020/29 .
  • F. DEN Hollander, W. König, R. Soares Dos Santos, The parabolic Anderson model on a Galton--Watson tree, in: In and Out of Equilibrium 3: Celebrating Vladas Sidovaricius, M.E. Vares, R. Fernandez, L.R. Fontes, C.M. Newman, eds., 77 of Progress in Probability, Birkhäuser, 2021, pp. 591--635, DOI 10.1007/978-3-030-60754-8_25 .
  • W. König, Branching random walks in random environment, in: Probabilistic Structures in Evolution, E. Baake, A. Wakolbinger, eds., Probabilistic Structures in Evolution, EMS Series of Congress Reports, European Mathematical Society Publishing House, 2021, pp. 23--41, DOI 10.4171/ECR/17-1/2 .
  • A. Zeghuzi, J.-P. Koester, M. Radziunas, H. Christopher, H. Wenzel, A. Knigge, Narrow lateral far field divergence obtained with spatially modulated broad-area lasers, in: 2021 27th International Semiconductor Laser Conference (ISLC), IEEE Xplore, IEEE, 2021, pp. 1--2, DOI 10.1109/ISLC51662.2021.9615888 .
  • R. Rossi, U. Stefanelli, M. Thomas, Rate-independent evolution of sets, in: Analysis of Evolutionary and Complex Systems: Issue on the Occasion of Alexander Mielke's 60th Birthday, M. Liero, S. Reichelt, G. Schneider, F. Theil, M. Thomas, eds., 14 of Discrete and Continuous Dynamical Systems -- Series S, American Institute of Mathematical Sciences, Springfield, 2021, pp. 89--119, DOI 10.3934/dcdss.2020304 .
  • A. Roche, U. Gowda, A. Kovalev, E. Viktorov, A. Pimenov, A.G. Vladimirov, M. Marconi, M. Giudici, G. Huyet, S. Slepneva, Defect mediated turbulence in a long laser, in: Real-time Measurements, Rogue Phenomena, and Single-Shot Applications VI, D.R. Solli, G. Herink, S. Bielawski, eds., 11671 of Proceedings of SPIE, SPIE. Digital Library, 2021, pp. 116710D/1--116710D/6, DOI 10.1117/12.2578727 .
  • A. Roche, U. Gowda, A. Kovalev, E. Viktorov, A. Pimenov, A.G. Vladimirov, M. Marconi, M. Giudici, G. Huyet, S. Slepneva, The formation of localised structures from the turn on transient of a long laser, in: Physics and Simulation of Optoelectronic Devices XXIX, B. Witzigmann, M. Osiński, Y. Arakawa, eds., 11680 of Proceedings of SPIE, SPIE Digital Library, 2021, pp. 116800N/1--116800N/6, DOI 10.1117/12.2578648 .
  • J.-J. Zhu, W. Jitkrittum, M. Diehl, B. Schölkopf, Kernel distributionally robust optimization: Generalized duality theorem and stochastic approximation, in: Proceedings of The 25th International Conference on Artificial Intelligence and Statistics, A. Banerjee, K. Fukumizu, eds., 130 of Proceedings of Machine Learning Research, 2021, pp. 280--288.
  • M. Bongarti, I. Lasiecka, Boundary stabilization of the linear MGT equation with feedback Neumann control, in: Deterministic and Stochastic Optimal Control and Inverse Problems, B. Jadamba, A.A. Khan, S. Migórski, M. Sama, eds., CRC Press, Boca Raton, 2021, pp. 150--169, DOI 10.1201/9781003050575 .
  • O. Marquardt, L. Geelhaar, O. Brandt, Wave-function engineering in In0.53Ga0.47As/InxAl1-xAs core/shell nanowires, in: 2021 International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD), IEEE Conference Publications Management Group, 2021, pp. 15--16, DOI 10.1109/NUSOD52207.2021.9541519 .
  • G. Nika, B. Vernescu, Micro-geometry effects on the nonlinear effective yield strength response of magnetorheological fluids, in: Emerging Problems in the Homogenization of Partial Differential Equations, P. Donato, M. Luna-Laynez, eds., 10 of SEMA SIMAI Springer Series, Springer, Cham, 2021, pp. 1--16, DOI 10.1007/978-3-030-62030-1_1 .
  • M. Horák, M. Kružík, P. Pelech, A. Schlömerkemper, Gradient polyconvexity and modeling of shape memory alloys, in: Variational Views in Mechanics, P.M. Mariano, ed., 46 of Advances in Mechanics and Mathematics, Birkhäuser, Cham, 2021, pp. 133--156, DOI 10.1007/978-3-030-90051-9_5 .
  • A. Stephan, EDP convergence for nonlinear fast-slow reaction systems, in: Report 29: Variational Methods for Evolution (hybrid meeting), A. Mielke, M. Peletier, D. Slepcev, eds., 17 of Oberwolfach Reports, European Mathematical Society Publishing House, Zurich, 2021, pp. 1456--1459, DOI 10.4171/OWR/2020/29 .