Publication

Accelerated And Inexact Forward-Backward Algorithms

Related publications (37)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Fréchet means in Wasserstein space

Yoav Zemel

This work studies the problem of statistical inference for Fréchet means in the Wasserstein space of measures on Euclidean spaces,

\mathcal W_2 ( \mathbb R^d )

. This question arises naturally from the problem of separating amplitude and phase variation i ...

EPFL2017

Accelerated And Inexact Forward-Backward Algorithms

Graph Chatbot

Chat with Graph Search

Exact Diffusion for Distributed Optimization and Learning-Part II: Convergence Analysis

Stochastic Zeroth-Order Optimisation Algorithms with Variance Reduction

Convex Optimization using Sparsified Stochastic Gradient Descent with Memory

Performance limits of stochastic sub-gradient learning, Part II: Multi-agent case

Mean-Field methods for Structured Deep-Learning in Computer Vision

Exact Diffusion for Distributed Optimization and Learning---Part II: Convergence Analysis

Asynchronous updates for stochastic gradient descent

Fréchet means in Wasserstein space

Stochastic Composite Least-Squares Regression with Convergence Rate O(1/n)

Multi-index stochastic collocation convergence rates for random PDEs with parametric regularity

Mean-Field methods for Structured Deep-Learning in Computer Vision

Fréchet means in Wasserstein space

Asynchronous updates for stochastic gradient descent

Exact Diffusion for Distributed Optimization and Learning-Part II: Convergence Analysis

Performance limits of stochastic sub-gradient learning, Part II: Multi-agent case

Exact Diffusion for Distributed Optimization and Learning---Part II: Convergence Analysis

Stochastic Composite Least-Squares Regression with Convergence Rate O(1/n)

Convex Optimization using Sparsified Stochastic Gradient Descent with Memory

Multi-index stochastic collocation convergence rates for random PDEs with parametric regularity

Stochastic Zeroth-Order Optimisation Algorithms with Variance Reduction