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Preprints im Fremdverlag 2020

  • D. Dvinskikh, A. Ogaltsov, A. Gasnikov, P. Dvurechensky, A. Tyurin, V. Spokoiny, Adaptive gradient descent for convex and non-convex stochastic optimization, Preprint no. arXiv:1911.08380, Cornell University, 2020.
  • E. Gorbunov, A. Rogozin, A. Beznosikov, D. Dvinskikh, A. Gasnikov, Recent theoretical advances in decentralized distributed convex optimization, Preprint no. arXiv:2011.13259, Cornell University, 2020.
  • D. Dvinskikh, A. Gasnikov, Decentralized and parallel primal and dual accelerated methods for stochastic convex programming problems, Preprint no. arXiv:1904.09015, Cornell University, 2020.
  • D. Dvinskikh, D. Tiapkin, Improved complexity bounds in Wasserstein barycenter problem, Preprint no. arXiv:2010.04677, Cornell University, 2020.
  • D. Dvinskikh, Stochastic approximation versus sample average approximation for population Wasserstein barycenter calculation, Preprint no. arXiv:2001.07697, Cornell University, 2020.
  • M. Danilova, P. Dvurechensky, A. Gasnikov, E. Gorbunov, S. Guminov, D. Kamzolov, I. Shibaev, Recent theoretical advances in non-convex optimization, Preprint no. arXiv:2012.06188, Cornell University, 2020.
  • A. Sadiev, A. Beznosikov, P. Dvurechensky, A. Gasnikov, Zeroth-order algorithms for smooth saddle-point problems, Preprint no. arXiv:2009.09908, Cornell University, 2020.
  • P. Dvurechensky, K. Safin, S. Shtern, M. Staudigl, Generalized self-concordant analysis of Frank--Wolfe algorithms, Preprint no. arXiv:2010.01009, Cornell University, 2020.
  • I. Shibaev, P. Dvurechensky, A. Gasnikov, Zeroth-order methods for noisy Hölder-gradient functions, Preprint no. arXiv:2006.11857, Cornell University, 2020.
  • P. Dvurechensky, S. Shtern, M. Staudigl, P. Ostroukhov, K. Safin, Self-concordant analysis of Frank--Wolfe algorithms, Preprint no. arXiv:2002.04320, Cornell University, 2020.
  • D. Tiapkin, A. Gasnikov, P. Dvurechensky, Stochastic saddle-point optimization for Wasserstein barycenters, Preprint no. arXiv:2006.06763, Cornell University, 2020.
  • N. Tupitsa, P. Dvurechensky, A. Gasnikov, C.A. Uribe , Multimarginal optimal transport by accelerated alternating minimization, Preprint no. arXiv:2004.02294, Cornell University Library, arXiv.org, 2020.
  • C. Bellingeri, P. Friz, M. Gerencsér, Singular paths spaces and applications, Preprint no. arXiv:2003.03352, Cornell University, 2020.
  • P. Friz, J. Gatheral, R. Radoičić, Forests, cumulants, martingales, Preprint no. arXiv:2002.01448, Cornell University, 2020.
  • P. Friz, P. Pigato, J. Seibel, The step stochastic volatility model (SSVM), Preprint no. May 7, Available at SSRN's eLibrary: urlhttps://ssrn.com/abstract=3595408 or urlhttp://dx.doi.org/10.2139/ssrn.3595408, 2020.
  • A. Rastogi, P. Mathé, Inverse learning in Hilbert scales, Preprint no. arXiv:2002.10208, Cornell University, 2020.
  • N. Puchkin, V. Spokoiny, E. Stepanov, D. Trevisan, Reconstruction of manifold embeddings into Euclidean spaces via intrinsic distances, Preprint no. arXiv:2012.13770, Cornell University, 2020.
  • N. Puchkin, A. Timofeev, V. Spokoiny, Manifold-based time series forecasting, Preprint no. arXiv:2012.08244, Cornell University, 2020.
  • S. Athreya, O. Butkovsky, K. Lê, L. Mytnik, Well-posedness of stochastic heat equation with distributional drift and skew stochastic heat equation, Preprint no. arXiv:2011.13498, Cornell University, 2020.
  • O. Butkovsky, K. Dareiotis , M. Gerencsér, Approximation of SDEs --- A stochastic sewing approach, Preprint no. arXiv:1909.07961, Cornell University, 2020.
  • A. Beznosikov, V. Samokhin, A. Gasnikov, Local SGD for saddle-point problems, Preprint no. arXiv:2010.13112, Cornell University, 2020.