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|Ordinal=5 | |Ordinal=5 | ||
|Type=Conference | |Type=Conference | ||
| − | | | + | |Official Website=https://dsaa2018.isi.it/home |
|City=Torino | |City=Torino | ||
| − | |Country= | + | |Country=Country:IT |
|Has coordinator=Laetitia Gauvin, Michele Tizzoni | |Has coordinator=Laetitia Gauvin, Michele Tizzoni | ||
|has general chair=Francesco Bonchi, Foster Provost | |has general chair=Francesco Bonchi, Foster Provost | ||
|has program chair=Tina Eliassi-Rad, Ciro Cattuto, Rayid Ghani | |has program chair=Tina Eliassi-Rad, Ciro Cattuto, Rayid Ghani | ||
|has tutorial chair=Gabriella Pasi, Richard De Veaux | |has tutorial chair=Gabriella Pasi, Richard De Veaux | ||
| − | |||
|has Proceedings Link=https://ieeexplore.ieee.org/xpl/conhome/8620128/proceeding | |has Proceedings Link=https://ieeexplore.ieee.org/xpl/conhome/8620128/proceeding | ||
|pageCreator=User:Curator 27 | |pageCreator=User:Curator 27 | ||
| Line 20: | Line 19: | ||
|Start Date=2018/10/01 | |Start Date=2018/10/01 | ||
|End Date=2018/10/03 | |End Date=2018/10/03 | ||
| + | |Event Status=as scheduled | ||
| + | |Event Mode=on site | ||
}} | }} | ||
| + | {{Event Deadline}} | ||
| + | {{Event Metric | ||
| + | |Number Of Accepted Papers=74 | ||
| + | }} | ||
| + | {{S Event}} | ||
Topics of interest include but are not limited to: | Topics of interest include but are not limited to: | ||
Foundations | Foundations | ||
Latest revision as of 13:08, 19 October 2022
The document "DSAA 2018" was published on "2022-10-19T13:08:42" on the website "ConfIDent" under the URL https://confident-conference.org/index.php/Event:DSAA 2018.
The document "DSAA 2018" describes an event in the sense of a conference.
The document "DSAA 2018" contains information about the event "DSAA 2018" with start date "2018/10/01" and end date "2018/10/03".
The event "DSAA 2018" is part of the event series identified by [[Event Series:DSAA]]
Deadlines
Metrics
Accepted Papers
74
Venue
Torino, Italy
Warning: Venue is missing. The map might not show the exact location.
Topics of interest include but are not limited to: Foundations
* Mathematical, probabilistic and statistical models and theories. * Machine learning theories, models and systems. * Knowledge discovery theories, models and systems. * Manifold and metric learning. * Deep learning and deep analytics. * Scalable analysis and learning. * Non-iid learning. * Heterogeneous data/information integration. * Data pre-processing, sampling and reduction. * Dimensionality reduction. * Feature selection, transformation and construction. * Large scale optimization. * High performance computing for data analytics. * Learning for streaming data. * Learning for structured and relational data. * Latent semantics and insight learning. * Mining multi-source and mixed-source information. * Mixed-type and structure data analytics. * Cross-media data analytics. * Big data visualization, modeling and analytics. * Multimedia/stream/text/visual analytics. * Relation, coupling, link and graph mining. * Personalization analytics and learning. * Web/online/social/network mining and learning. * Structure/group/community/network mining. * Cloud computing and service data analysis. * * Management, storage, retrieval and search * * Cloud architectures and cloud computing. * Data warehouses and large-scale databases. * Memory, disk and cloud-based storage and analytics. * Distributed computing and parallel processing. * High performance computing and processing. * Information and knowledge retrieval, and semantic search. * Web/social/databases query and search. * Personalized search and recommendation. * Human-machine interaction and interfaces. * Crowdsourcing and collective intelligence. * * Theoretical Foundations for Social issues * * Data science meets social science. * Security, trust and risk in big data. * Data integrity, matching and sharing. * Privacy and protection standards and policies. * Privacy preserving big data access/analytics. * Fairness and transparency in data science.
