Adaptation, Learning, and Optimization over Networks
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
We developed an in vitro protein expression and interaction analysis platform based on a highly parallel and sensitive microfluidic affinity assay, and used it for 14,792 on-chip experiments, which exhaustively measured the protein-protein interactions of ...
Route choice models are difficult to design and to estimate for various reasons. In this paper we focus on issues related to data. Indeed, real data in its original format are not related to the network used by the modeler and do therefore not correspond t ...
In many wired and wireless networks, nodes process input traffic to satisfy a network constraint (e.g., a capacity constraint) and to increase the utility of data in the output flows given these constraints. In this paper we focus on the special case in wh ...
Many structured overlay networks rely on a ring invariant as a core network connectivity element. The responsibility ranges of the participating peers and navigability principles (greedy routing) heavily depend on the ring structure. For correctness guaran ...
An initialization mechanism is presented for Kohonen neural network implemented in CMOS technology. Proper selection of initial values of neurons’ weights has a large influence on speed of the learning algorithm and finally on the quantization error of the ...
Multi Agent Systems (MAS) have recently attracted a lot of interest because of their ability to model many real life scenarios where information and control are distributed among a set of different agents. Practical applications include planning, schedulin ...
In this paper we develop a multi-agent simulation model to explore the issue of learning in interorganizational networks. Though interorganizational network researchers generally agree that when firms form into networks they will gain access to new knowled ...
Sensor networks measuring correlated data are considered, where the task is to gather data from the network nodes to a sink. A specific scenario is addressed, where data at nodes are lossy coded with high-resolution, and the information measured by the nod ...
Distributed adaptive algorithms are proposed based on incremental and diffusion strategies. Adaptation rules that are suitable for ring topologies and general topologies are described. Both distributed LMS and RLS implementations are considered in order to ...
Route choice models are difficult to design and to estimate for various reasons. In this paper we focus on issues related to data. Indeed, real data in its original format are not related to the network used by the modeler and do therefore not correspond t ...
