Towards Proximity Graph Auto-configuration: An Approach Based on Meta-learning

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	ADBIS (24. : 2020 : Online) Advances in databases and information systems
1. Verfasser:	Oyamada, Rafael Seidi (VerfasserIn)
Weitere Verfasser:	Shimomura, Larissa C. (VerfasserIn), Junior, Sylvio Barbon (VerfasserIn), Kaster, Daniel S. (VerfasserIn)
Format:	UnknownFormat
Sprache:	eng
Veröffentlicht:	2020
Schlagworte:
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Titel	Jahr	Verfasser
Can We Probabilistically Generate Uniformly Distributed Relation Instances Efficiently?	2020	Biskup, Joachim
Iterations for Propensity Score Matching in MonetDB	2020	Böhlen, Michael H.
Context-Free Path Querying by Kronecker Product	2020	Orachev, Egor
Integrating (Very) Heterogeneous Data Sources: A Structured and an Unstructured Perspective	2020	Manolescu, Ioana
Blockchains and Databases: Opportunities and Challenges for the Permissioned and the Permissionless	2020	Agrawal, Divyakant
Pattern Sampling in Distributed Databases	2020	Diop, Lamine
Towards Proximity Graph Auto-configuration: An Approach Based on Meta-learning	2020	Oyamada, Rafael Seidi
Fake News Detection Based on Subjective Opinions	2020	Zhang, Danchen
Distributed Tree-Pattern Matching in Big Data Analytics Systems	2020	Diestelkämper, Ralf
Template-Based Multi-solution Approach for Data-to-Text Generation	2020	Mota, Abelardo Vieira
An Efficient Index for Reachability Queries in Public Transport Networks	2020	Tesfaye, Bezaye
The Tell-Tale Cube	2020	Chédin, Antoine
Processing Temporal and Time Series Data: Present State and Future Challenges	2020	Gamper, Johann
Upper Bound on the Size of FP-Tree	2020	Shahbazi, Nima
Improving on Coalitional Prediction Explanation	2020	Ferrettini, Gabriel
JSON Functionally	2020	Pokorný, Jaroslav