Zobrazeno 1 - 10
of 294
pro vyhledávání: '"Olteanu, Dan"'
Autor:
Scheerer, Jan Luca, Lykov, Anton, Kayali, Moe, Fountalis, Ilias, Olteanu, Dan, Vasiloglou, Nikolaos, Suciu, Dan
We demonstrate QirK, a system for answering natural language questions on Knowledge Graphs (KG). QirK can answer structurally complex questions that are still beyond the reach of emerging Large Language Models (LLMs). It does so using a unique combin
Externí odkaz:
http://arxiv.org/abs/2408.07494
Autor:
Olteanu, Dan
We overview recent progress on the longstanding problem of incremental view maintenance (IVM), with a focus on the fine-grained complexity and optimality of IVM for classes of conjunctive queries. This theoretical progress guided the development of I
Externí odkaz:
http://arxiv.org/abs/2404.17679
We investigate the evaluation of conjunctive queries over static and dynamic relations. While static relations are given as input and do not change, dynamic relations are subject to inserts and deletes. We characterise syntactically three classes of
Externí odkaz:
http://arxiv.org/abs/2404.16224
We study the dynamic query evaluation problem: Given a full conjunctive query Q and a sequence of updates to the input database, we construct a data structure that supports constant-delay enumeration of the tuples in the query output after each updat
Externí odkaz:
http://arxiv.org/abs/2312.09331
Quantifying the contribution of database facts to query answers has been studied as means of explanation. The Banzhaf value, originally developed in Game Theory, is a natural measure of fact contribution, yet its efficient computation for select-proj
Externí odkaz:
http://arxiv.org/abs/2308.05588
The performance of worst-case optimal join algorithms depends on the order in which the join attributes are processed. Selecting good orders before query execution is hard, due to the large space of possible orders and unreliable execution cost estim
Externí odkaz:
http://arxiv.org/abs/2307.16540
In this paper we investigate the problem of quantifying the contribution of each variable to the satisfying assignments of a Boolean function based on the Shapley value. Our main result is a polynomial-time equivalence between computing Shapley value
Externí odkaz:
http://arxiv.org/abs/2306.14211
Estimating the output size of a query is a fundamental yet longstanding problem in database query processing. Traditional cardinality estimators used by database systems can routinely underestimate the true output size by orders of magnitude, which l
Externí odkaz:
http://arxiv.org/abs/2306.14075
We apply foundation models to data discovery and exploration tasks. Foundation models include large language models (LLMs) that show promising performance on a range of diverse tasks unrelated to their training. We show that these models are highly a
Externí odkaz:
http://arxiv.org/abs/2306.09610
This article describes F-IVM, a unified approach for maintaining analytics over changing relational data. We exemplify its versatility in four disciplines: processing queries with group-by aggregates and joins; learning linear regression models using
Externí odkaz:
http://arxiv.org/abs/2303.08583