Publications related to Complexity Certification of the Fast Alternating Minimization Algorithm for Linear Model Predictive Control

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

A first-order primal-dual method with adaptivity to local smoothness

Volkan Cevher, Maria-Luiza Vladarean

We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

2021

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Ali H. Sayed, Kun Yuan, Sulaiman A S A E Alghunaim

This article studies a class of nonsmooth decentralized multiagent optimization problems where the agents aim at minimizing a sum of local strongly-convex smooth components plus a common nonsmooth term. We propose a general primal-dual algorithmic framewor ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization

Ali H. Sayed, Kun Yuan

This paper introduces a new algorithm for consensus optimization in a multi-agent network, where all agents collaboratively find a minimizer for the sum of their private functions. All decentralized algorithms rely on communications between adjacent nodes. ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Decentralized Nonlinear Model Predictive Control for 3D Formation of Multirotor Micro Aerial Vehicles with Relative Sensing and Estimation

Alcherio Martinoli, Izzet Kagan Erünsal, Rodrigo Martins de Matos Ventura

In recent years, extensive research is conducted on the coordination and cooperation strategies of multirotor Micro Aerial Vehicles (MAVs) to perform high-level missions such as scientific exploration, search and rescue, intelligence gathering etc. [1], [2 ...

2019

Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures

Hakan Gökcesu, Kaan Gökcesu

We propose an online algorithm for sequential learning in the contextual multiarmed bandit setting. Our approach is to partition the context space and, then, optimally combine all of the possible mappings between the partition regions and the set of bandit ...

2019

Delay-Power-Rate-Distortion Optimization of Video Representations for Dynamic Adaptive Streaming

Pascal Frossard, Laura Toni, Chenglin Li

Dynamic adaptive streaming addresses user heterogeneity by providing multiple encoded representations at different rates and/or resolutions for the same video content. For delay-sensitive applications, such as live streaming, there is however a stringent r ...

IEEE2018

Generic Round-Function-Recovery Attacks for Feistel Networks over Small Domains

Serge Vaudenay, Fatma Betül Durak

Feistel Networks (FN) are now being used massively to encrypt credit card numbers through format-preserving encryption. In our work, we focus on FN with two branches, entirely unknown round functions, modular additions (or other group operations), and when ...

2018

Generic Round-Function-Recovery Attacks for Feistel Networks over Small Domains

Serge Vaudenay, Fatma Betül Durak

Feistel Networks (FN) are now being used massively to encrypt credit card numbers through format-preserving encryption. In our work, we focus on FN with two branches, entirely unknown round functions, modular additions (or other group operations), and when ...

ePrint2018

When Stuck, Flip a Coin

Slobodan Mitrovic

Many modern services need to routinely perform tasks on a large scale. This prompts us to consider the following question: How can we design efficient algorithms for large-scale computation? In this thesis, we focus on devising a general strategy to addr ...

EPFL2018

Complexity Certification of the Fast Alternating Minimization Algorithm for Linear Model Predictive Control

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

A first-order primal-dual method with adaptivity to local smoothness

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization

Decentralized Nonlinear Model Predictive Control for 3D Formation of Multirotor Micro Aerial Vehicles with Relative Sensing and Estimation

Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures

Delay-Power-Rate-Distortion Optimization of Video Representations for Dynamic Adaptive Streaming

Generic Round-Function-Recovery Attacks for Feistel Networks over Small Domains

Generic Round-Function-Recovery Attacks for Feistel Networks over Small Domains

When Stuck, Flip a Coin

A first-order primal-dual method with adaptivity to local smoothness

Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization

Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Decentralized Nonlinear Model Predictive Control for 3D Formation of Multirotor Micro Aerial Vehicles with Relative Sensing and Estimation

Generic Round-Function-Recovery Attacks for Feistel Networks over Small Domains

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Generic Round-Function-Recovery Attacks for Feistel Networks over Small Domains

Delay-Power-Rate-Distortion Optimization of Video Representations for Dynamic Adaptive Streaming

When Stuck, Flip a Coin