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Capacity of Deterministic Z-Chain Relay-Interference Network

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When Neurons Fail - Technical Report

Rachid Guerraoui, El Mahdi El Mhamdi

Neural networks have been traditionally considered robust in the sense that their precision degrades gracefully with the failure of neurons and can be compensated by additional learning phases. Nevertheless, critical applications for which neural networks ...

EPFL2016

On Multi-Dimensional Privacy in Context-Aware Mobile Networks

Igor Bilogrevic

By the end of 2013, the number of internet-connected mobile devices is expected to exceed that of humans. Omnipresent and context-aware, mobile devices enable people to communicate and exchange data anytime and almost anywhere. The myriad of ”digital footp ...

EPFL2014

Deep Learning via Semi-Supervised Embedding

Ronan Collobert

We show how nonlinear embedding algorithms popular for use with "shallow" semi-supervised learning techniques such as kernel methods can be easily applied to deep multi-layer architectures, either as a regularizer at the output layer, or on each layer of t ...

Springer2012

Capacity of Deterministic Z-Chain Relay-Interference Network

Christina Fragouli, Suhas Diggavi

The wireless multiple-unicast problem is considered over a layered network, where the rates of transmission are limited by the relaying and interference effect. The deterministic model introduced in 131 is used to capture the broadcasting and multiple acce ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Multiple task learning in recurrent neural networks using layered reservoirs

Martin Hasler, Ali Ajdari Rad, Mahdi Jalili

In this paper, to learn multiple tasks sharing same inputs, a two-layer architecture for a reservoir based recurrent neural network is proposed. The inputs are fed into the general workspace layer where the weights are adapted to provide maximum informatio ...

2009

Distributed semantics and implementation for systems with interaction and priority

Joseph Sifakis

The paper studies a distributed implementation method for the BIP (Behavior, Interaction, Priority) component framework for modeling heterogeneous systems. BIP offers two powerful mechanisms for describing composition of components by combining interaction ...

2008

Interference management in impulse-radio ultra-wide band networks

Ruben Merz

We consider networks of impulse-radio ultra-wide band (IR-UWB) devices. We are interested in the architecture, design, and performance evaluation of these networks in a low data-rate, self-organized, and multi-hop setting. IR-UWB is a potential physical la ...

EPFL2008

Distributed and Component Oriented Tools for Communication Networks Using Web Services

Sébastien Rumley, Christian Gaumier, Christophe Trefois

Modern communication networks are reaching a high level of complexity. As their global dimensioning and performance evaluation are very hard tasks, a multi-layer approach is generally applied to divide them in smaller problems easier to tackle. Within this ...

ARGESIM2007

Compositional reflectance and transmittance model for multilayer specimens

Roger Hersch, Mathieu Hébert

We propose a compositional model for predicting the reflectance and the transmittance of multilayer specimens composed of layers having possibly distinct refractive indices. The model relies on the laws of geometrical optics and on a description of the mul ...

2007

Layered Complex Networks

Patrick Thiran, Maciej Kurant

Many complex networks are only a part of larger systems, where a number of coexisting topologies interact and depend on each other. We introduce a layered model to facilitate the description and analysis of such systems. As an example of its application, w ...

2006