This paper considers the problem of querying dirty databases, which may contain both erroneous facts and multiple names for the same entity. While both of these data quality issues have been widely studied in isolation, our contribution is a holistic framework for jointly deduplicating and...
04b Atto di convegno in volume
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The Datalog query language can express several powerful recursive properties, often crucial in real-world scenarios. While answering such queries is feasible over relational databases, the picture changes dramatically when data is enriched with intensional knowledge. It is indeed well-known that...
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Landslides are critical natural hazards whose frequency and severity are increasing due to climate change and human activities. The consequences of landslides are severe and can lead to the destruction of homes, infrastructures and the contamination of water supplies, with severe impact also on the...
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Deep image inpainting is a computer vision task that uses Deep Neural Networks to generate plausible content to complete an image, for example for the restoration of a damaged image or the removal of unwanted elements captured in the picture. This paper uses deep image inpainting to restore...
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In recent years, stock price forecasting has become a challenging task commonly used to evaluate the performance of various machine learning solutions. This work explores a Federated Learning (FL) framework within a competitive collaboration scenario with the aim of training a centralised model...
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Having access to a reliable and accurate prediction of the short-term power demand is a fundamental step for the widespread adoption of Electric Vehicles (EVs), as their charges may have a significant impact on the power system balancing. In this direction, we propose a short-term load demand...
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This paper proposes a Multi-Agent Reinforcement Learning (MARL) algorithm for the multi-robot navigation problem. Most of the proposals in the literature requires some form of information sharing and communications among agents to coordinate their action in order to complete the overall task. The...
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Consensus of multi-agent systems has recently been studied in the context of Federated Learning (FL), an emerging branch of distributed machine learning. The present paper proposes a two-level hierarchical algorithm for FL in the context of edge computing, developing a fully decentralized solution...
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We introduce Strategy Repair, the problem of finding a minimal amount of modifications to turn a strategy for a reachability game from losing into winning. The problem is relevant for a number of settings in Planning and Synthesis, where solutions essentially correspond to winning strategies in a...
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Answering temporal CQs over temporalized Description Logic knowledge bases (TKB) is a main technique to realize ontology-based situation recognition. In case the collected data in such a knowledge base is inaccurate, important query answers can be missed. In this paper we introduce the TKB...