Stochastic Quasi-Gradient Methods: Variance Reduction via Jacobian Sketching

(32:36)

Stochastic Quasi-Newton Methods for Online Learning

(58:43)

Aryan Mokhtari presents \

(39:46)

Stochastic Quasi-Newton Methods for Online Learning

(58:43)

Quasi-strategies in stochastic evolutionary games

(50:11)

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(47:44)

Rongchan Zhu (Univiersity of Bielefeld) / The stochastic quasi-geostrophic equation

(25:35)

Stochastic Quasi Newton Methods

(47)

UQ Hybrid Seminar - Talk by Dr. André Carlon, KAUST

(37:35)

André Gustavo Carlon – Stochastic Optimization for Bayesian Design of Experiments

(25:40)

TNRG talk #13: SketchySGD: Reliable Stochastic Optimization via Randomized Curvature Estimates

(58:31)

François-Xavier Briol – Learning to Reduce Variance Using Stochastic Gradient Descent

(27:2)

Máté Gerencsér – Approximation of SDEs – a stochastic sewing approach

(28:14)

A Stochastic Newton Algorithm for Distributed Convex Optimization

(35:11)

Gunther Leobacher: Quasi Monte Carlo Methods and their Applications

(49:45)

Roi Baer - Stochastic Vector Methods for extended systems - IPAM at UCLA

(54:42)

Stochastic dynamics using Quasi-elastic neutron scattering (QENS) Molecular dynamics simulation

(57:41)

Felix Otto: Singular quasi-linear stochastic PDEs II

(1:22:48)

QPL2017 - John van de Wetering. Quantum theory is a quasi-stochastic process theory

(19:35)

Benedict Leimkuhler – Stochastic models and numerical methods with applications to machine learning

(33:51)