no code implementations • 20 Feb 2024 • Fabian Schaipp, Guillaume Garrigos, Umut Simsekli, Robert Gower
We then derive iterative methods based on the stochastic proximal point method for computing the geometric median and generalizations thereof.
1 code implementation • 28 Dec 2023 • Farshed Abdukhakimov, Chulu Xiang, Dmitry Kamzolov, Robert Gower, Martin Takáč
Adaptive optimization methods are widely recognized as among the most popular approaches for training Deep Neural Networks (DNNs).
2 code implementations • NeurIPS 2023 • Chirag Modi, Charles Margossian, Yuling Yao, Robert Gower, David Blei, Lawrence Saul
We study how GSM-VI behaves as a function of the problem dimensionality, the condition number of the target covariance matrix (when the target is Gaussian), and the degree of mismatch between the approximating and exact posterior distribution.
no code implementations • NeurIPS 2023 • Justin Domke, Guillaume Garrigos, Robert Gower
Black-box variational inference is widely used in situations where there is no proof that its stochastic optimization succeeds.
no code implementations • NeurIPS 2019 • Robert Gower, Dmitry Koralev, Felix Lieder, Peter Richtarik
We develop a randomized Newton method capable of solving learning problems with huge dimensional feature spaces, which is a common setting in applications such as medical imaging, genomics and seismology.
2 code implementations • 9 Sep 2019 • Robert Gower, Denali Molitor, Jacob Moorman, Deanna Needell
We present new adaptive sampling rules for the sketch-and-project method for solving linear systems.
Numerical Analysis Numerical Analysis 15A06, 15B52, 65F10, 68W20, 65N75, 65Y20, 68Q25, 68W40, 90C20