Séminaire Valda : Paul Boniol

28 novembre 2022, 14:00-15:00. ENS, S16. Detection of Anomalies and Identification of their Precursors in Large Data Series Collections Extensive collections of data series are becoming a reality in many scientific and social domains, such as environmental sciences, astrophysics, neurosciences, and engineering. Informally, a data series is an ordered sequence…

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Séminaire Valda : Dan Suciu

4 novembre 2022, 10:30-11:30. ENS, S16. Datalog: Optimizations and Extensions Modern data analytics requires iteration, yet relational database engines are mostly optimized for non-recursive queries. SQL supports only a limited form of recursion. A better formalism for recursive queries is datalog, which has some elegant properties (recursion always terminates), and…

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Séminaire Valda : Camille Bourgaux

3 juin 2022, 10:30-11:30. ENS, Hauts du DI. Querying inconsistent prioritized data with ORBITS: Algorithms, implementation, and experiments We investigate practical algorithms for inconsistency-tolerant query answering over prioritized knowledge bases, which consist of a logical theory, a set of facts, and a priority relation between conflicting facts. We consider three…

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Séminaire Valda : Yann Ramusat

12 avril 2022, 10:30-11:30. ENS, S16 The Semiring-Based Provenance Framework for Graph Databases L’augmentation du volume de données collectées par des capteurs et générées par des interactions humaines a mené à l’utilisation des bases de données orientées graphes en tant que modèle de représentation efficace pour les données complexes. Les…

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Séminaire Valda : Michaël Thomazo

8 avril 2022, 10:30-11:30. ENS, S16 Capturing Homomorphism-Closed Decidable Queries with Existential Rules Existential rules are a well studied ontology-mediated query language for which the chase represents a generic computational approach for query answering. It is straightforward that existential rule queries exhibiting chase termination are decidable and can only recognize…

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Séminaire Valda : Debabrota Basu

Debabrota Basu, Inria Lille. 11 mars 2022, 10:30-11:30. ENS S16. Verifying and Explaining Unfairness of Machine Learning Algorithms In recent years, machine learning (ML) algorithms have been deployed in safety-critical and high-stake decision-making, where the fairness or unbiasedness of algorithms bears significant importance. Fairness in ML centres on detecting bias…

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