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The exploration of a data set consists in grouping similar data. The classical statistical methods often fail when there is is no minimal assumption on the clusters. Our approach is based on the links between data, but the pairwise comparison between data and the importance of the links depend heavily on context where data lies. We propose to analyze a dataset through methods of the social choice...
In the context of multiplayer games, the parallel repetition problem can be phrased as follows: given a game $G$ with optimal winning probability $1-\alpha $ and its repeated version $G^{n}$ (in which $n$ games are played together, in parallel), can the players use strategies that are substantially better than ones in which each game is played independently? This question is relevant in physics...
Appropriately defining and then efficiently calculating similarities from large data sets are often essential in data mining, both for building tractable representations and for gaining understanding of data and generating processes. Here we rely on the premise that given a set of objects and their correlations, each object is characterized by its context, i.e. its correlations to the other objects,...
Increasing numbers of sensors are being deployed in environments to monitor our behaviours and environmental phenomena. Missing data is an inevitable problem in almost every sensorised environment, due to physical failure, poor connection, or dislodgement. This results in an incomplete view of the real-world, leading to poor prediction and consequently, degraded quality of system services. This paper...
Furthering the study of cryptography in constant parallel time, we give new evidence for the security of Gold Reich's candidate pseudorandom generator with near-optimal, polynomial stretch. Our evidence consists both of security against sub exponential-time linear attacks as well as sub exponential-time attacks using SDP hierarchies such as Sherali-Adams+ and Lasserre/Parrilo. More specifically, instantiating...
To help analysts sift through large numbers of documents, we suggest an auto-highlighting system that computationally identifies the topmost salient sentences in each document as a form of summary and rapid comprehension aid. We conducted a user study to gather data about the types of sentences people highlight when reading and comprehending text. Our study focuses not only on the comparison between...
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