Concept

Multitâche

Publications associées (46)

A Regularization Framework for Learning Over Multitask Graphs

Ali H. Sayed, Stefan Vlaski, Roula Nassif

This letter proposes a general regularization framework for inference over multitask networks. The optimization approach relies on minimizing a global cost consisting of the aggregate sum of individual costs regularized by a term that allows to incorporate ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

A Scalable and Secure System Architecture for Smart Buildings

Georgios Lilis

Recent years has seen profound changes in building technologies both in Europe and worldwide. With the emergence of Smart Grid and Smart City concepts, the Smart Building has attracted considerable attention and rapid development. The introduction of novel ...

EPFL2017

Decentralized Clustering and Linking by Networked Agents

Ali H. Sayed, Ali Zoubir

We consider the problem of decentralized clustering and estimation over multitask networks, where agents infer and track different models of interest. The agents do not know beforehand which model is generating their own data. They also do not know which a ...

IEEE2017

Capture-Point Based Balance and Reactive Omnidirectional Walking Controller

Aude Billard, Michael Bosongo Bombile

This paper proposes a capture-point based reactive omnidirectional controller for bipedal locomotion. The proposed scheme, formulated within Model Predictive Control (MPC) framework, exploits concurrently the Center of Mass (CoM) and Capture Point (CP) dyn ...

2017

Diffusion LMS over multitask networks with noisy links

Ali H. Sayed, Jie Chen, Roula Nassif

Diffusion LMS is an efficient strategy for solving distributed optimization problems with cooperating agents. In some applications, the optimum parameter vectors may not be the same for all agents. Moreover, agents usually exchange information through nois ...

IEEE2016

Distributed learning over multitask networks with linearly related tasks

Ali H. Sayed, Roula Nassif

In this work, we consider distributed adaptive learning over multitask mean-square-error (MSE) networks where each agent is interested in estimating its own parameter vector, also called task, and where the tasks at neighboring agents are related according ...

IEEE2016

A Multi-Core Reconfigurable Architecture for Ultra-Low Power Bio-Signal Analysis

David Atienza Alonso, Giovanni Ansaloni, Ruben Braojos Lopez, Soumya Subhra Basu, Loris Gérard Duch

This paper introduces a novel computing architecture devoted to the ultra-low power analysis of multiple bio-signals. Its structure comprises several processors interfaced with a shared acceleration resource, implemented as a Coarse Grained Reconfigurable ...

2016

The IX Operating System: Combining Low Latency, High Throughput, and Efficiency in a Protected Dataplan

Edouard Bugnion, Christos Kozyrakis, Georgios Prekas, Mia Primorac, Ana Klimovic

The conventional wisdom is that aggressive networking requirements, such as high packet rates for small messages and μs-scale tail latency, are best addressed outside the kernel, in a user-level networking stack. We present ix, a dataplane operating system ...

Association for Computing Machinery2016

Diffusion LMS Over Multitask Networks

Ali H. Sayed, Jie Chen

The diffusion LMS algorithm has been extensively studied in recent years. This efficient strategy allows to address distributed optimization problems over networks in the case where nodes have to collaboratively estimate a single parameter vector. Neverthe ...

Institute of Electrical and Electronics Engineers2015

Adaptive clustering for multitask diffusion networks

Ali H. Sayed, Jie Chen

Diffusion LMS was originally conceived for online distributed parameter estimation in single-task environments where agents pursue a common objective. However, estimating distinct but correlated objects (multitask problems) is useful in many applications. ...

IEEE2015

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