Spotlight talks from paper submissions
in
Workshop: Beyond first order methods in machine learning systems

Spotlight talks

Damien Scieur · Konstantin Mishchenko · Rohan Anil

2019 Spotlight talks from paper submissions
in
Workshop: Beyond first order methods in machine learning systems

Abstract

Symmetric Multisecant quasi-Newton methods. Damien Scieur (Samsung AI Research Montreal); Thomas Pumir (Princeton University); Nicolas Boumal (Princeton University)

Stochastic Newton Method and its Cubic Regularization via Majorization-Minimization. Konstantin Mishchenko (King Abdullah University of Science & Technology (KAUST)); Peter Richtarik (KAUST); Dmitry Koralev (KAUST)

Full Matrix Preconditioning Made Practical. Rohan Anil (Google); Vineet Gupta (Google); Tomer Koren (Google); Kevin Regan (Google); Yoram Singer (Princeton)

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