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Mixing of Hamiltonian Monte Carlo on strongly log-concave distributions 2: Numerical integrators

Publications associées (33)

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Localization errors of the stochastic heat equation

David Jean-Michel Candil

In this thesis, we study the stochastic heat equation (SHE) on bounded domains and on the whole Euclidean space

\R^d.

We confirm the intuition that as the bounded domain increases to the whole space, both solutions become arbitrarily close to one another ...

EPFL2022

Mixing of Hamiltonian Monte Carlo on strongly log-concave distributions 2: Numerical integrators

Graph Chatbot

Chattez avec Graph Search

Localization errors of the stochastic heat equation

An Accelerated First-Order Method for Non-convex Optimization on Manifolds

AKSEL: Fast Byzantine SGD

Complexity analysis of stochastic gradient methods for PDE-constrained optimal control problems with uncertain parameters

Learning Generalized Nash Equilibria in a Class of Convex Games

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

Improved stability of optimal traffic paths

Testing Graph Clusterability: Algorithms and Lower Bounds

Design and Performance Evaluation of an Infotaxis-Based Three-Dimensional Algorithm for Odor Source Localization

Improved stability of optimal traffic paths

Learning Generalized Nash Equilibria in a Class of Convex Games

An Accelerated First-Order Method for Non-convex Optimization on Manifolds

Localization errors of the stochastic heat equation

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

Testing Graph Clusterability: Algorithms and Lower Bounds

Design and Performance Evaluation of an Infotaxis-Based Three-Dimensional Algorithm for Odor Source Localization

AKSEL: Fast Byzantine SGD

Complexity analysis of stochastic gradient methods for PDE-constrained optimal control problems with uncertain parameters

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization