Concept
Itération
Publications associées (25)
An adaptive primal-dual framework for nonsmooth convex minimization
Volkan Cevher, Quoc Tran Dinh, Ahmet Alacaoglu
We propose a new self-adaptive and double-loop smoothing algorithm to solve composite, nonsmooth, and constrained convex optimization problems. Our algorithm is based on Nesterov’s smoothing technique via general Bregman distance functions. It self-adaptiv ...
2019Expectation propagation in the large data limit
Guillaume Philippe Ivan Joseph Dehaene
Expectation propagation (EP) is a widely successful algorithm for variational inference. EP is an iterative algorithm used to approximate complicated distributions, typically to find a Gaussian approximation of posterior distributions. In many applications ...
Wiley2018Distributed Modifier-Adaptation Schemes for the Real-Time Optimization of Interconnected Systems in the Presence of Structural Plant-Model Mismatch
Dominique Bonvin, René Uwe Schneider, Predrag Milosavljevic
The desire to operate chemical processes in a safe and economically optimal way has motivated the development of so-called real-time optimization (RTO) methods [1]. For continuous processes, these methods aim to compute safe and optimal steady-state set ...
2016Disparity and Optical Flow Partitioning Using Extended Potts Priors
This paper addresses the problems of disparity and optical flow partitioning based on the brightness invariance assumption. We investigate new variational approaches to these problems with Potts priors and possibly box constraints. For the optical flow par ...
IMA2015Towards Predicting the Runtime of Iterative Analytics with PREDIcT
Anastasia Ailamaki, Adrian Daniel Popescu
Machine learning algorithms are widely used today for analytical tasks such as data cleaning, data categorization, or data filtering. At the same time, the rise of social media motivates recent uptake in large scale graph processing. Both categories of alg ...
EPFL2013