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Distributed classification of multiple observation sets by consensus

Publications associées (67)

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Tactile sensing transfers complex interactive information in a most intuitive sense. Such a populated set of data from the environment and human interactions necessitates various degrees of information from both modular and distributed areas. A sensor desi ...

Institute of Physics2015

Learning decision rules for energy efficient building control

Colin Neil Jones

While rule based control (RBC) is current practice in most building automation systems that issue discrete control signals, recent simulation studies suggest that advanced, optimization based control methods such as hybrid model predictive control (HMPC) c ...

Elsevier2014

Rate allocation and optimized decoding in inter-session network coding

Eirina Bourtsoulatze

Recent advances in data processing and communication systems have led to a continuous increase in the amount of data communicated over today’s networks. These large volumes of data pose new challenges on the current networking infrastructure that only offe ...

EPFL2013

An epidemic spreading in a network calls for a decision on the part of the network members: They should decide whether to protect themselves or not. Their decision depends on the trade-off between their perceived risk of being infected and the cost of bein ...

Institute of Electrical and Electronics Engineers2013

This work shows how the combination weights of diffusion strategies for adaptation and learning over networks can be chosen in order for the network mean-square-error performance to match that of an optimized centralized (or batch) solution. The results sh ...

IEEE2013

Coordination and Sampling in Distributed Constraint Optimization

Brammert Ottens

The Distributed Constraint Optimization (DCOP) framework can be used to model a wide range of optimization problems that are inherently distributed. A distributed optimization problem can be viewed as a problem distributed over a set of agents, where agent ...

EPFL2012

Paradoxical Evidence Integration in Rapid Decision Processes

Michael Herzog, Wulfram Gerstner, Johannes Rüter, Nicolas Marcille

Decisions about noisy stimuli require evidence integration over time. Traditionally, evidence integration and decision making are described as a one-stage process: a decision is made when evidence for the presence of a stimulus crosses a threshold. Here, w ...

Public Library of Science2012

An epidemic spreading in a network calls for a decision on the part of the network members: They should decide whether to protect themselves or not. Their decision depends on the trade off between their perceived risk of being infected and the cost of bein ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Inference from data is of key importance in many applications of informatics. The current trend in performing such a task of inference from data is to utilise machine learning algorithms. Moreover, in many applications that it is either required or is pref ...

EPFL2011

Decision making is of crucial interest in many disciplines such as psychology, neuroscience, economics and machine learning. Binary perceptual decision theories relate to situations where an observer (or machine) is confronted with one of two possible nois ...

EPFL2011