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Most people believe that renaming is easy: simply choose a name at random; if more than one process selects the same name, then try again. We highlight the issues that occur when trying to implement such a scheme and shed new light on the read-write complexity of randomized renaming in an asyn-chronous environment. At the heart of our new perspective stands… (More)

—The aim of this paper is to show that spatial coupling can be viewed not only as a means to build better graphical models, but also as a tool to better understand uncoupled models. The starting point is the observation that some asymptotic properties of graphical models are easier to prove in the case of spatial coupling. In such cases, one can then use… (More)

This paper defines the problem of Scalable Secure Computing in a Social network: we call it the S 3 problem. In short, nodes, directly reflecting on associated users, need to compute a function f : V → U of their inputs in a set of constant size, in a scalable and secure way. Scalability means that the message and computational complexity of the distributed… (More)

These notes review six lectures given by Prof. Andrea Montanari on the topic of statistical estimation for linear models. The first two lectures cover the principles of signal recovery from linear measurements in terms of minimax risk. Subsequent lectures demonstrate the application of these principles to several practical problems in science and… (More)

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