Toward Massive Query Optimization in Large-Scale Distributed Stream Systems

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A plethora of real world problems consist of a number of agents that interact, learn, cooperate, coordinate, and compete with others in ever more complex environments. Examples include autonomous vehicles, robotic agents, intelligent infrastructure, IoT de ...

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Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

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Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

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In the domains of machine learning, data science and signal processing, graph or network data, is becoming increasingly popular. It represents a large portion of the data in computer, transportation systems, energy networks, social, biological, and other s ...

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Science Communication Desperately Needs More Aligned Recommendation Algorithms

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With 1 billion watch-time hours per day, YouTube now plays a major role in communication. Unfortunately, a large amount of misinformation is produced and widely shared on this platform (Donzelli et al., 2018; Allgaier, 2019; Loeb et al., 2019). In this pap ...

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