Results 261 to 270 of about 23,742,502 (301)

On active learning for data acquisition

2002 IEEE International Conference on Data Mining, 2002. Proceedings., 2003
Many applications are characterized by having naturally incomplete data on customers - where data on only some fixed set of local variables is gathered However, having a more complete picture can help build better models. The naive solution to this problem - acquiring complete data for all customers s often impractical due to the costs of doing so.
Zhiqiang Zheng 0004, Balaji Padmanabhan
openaire   +1 more source

Detecting activation in fMRI data

Statistical Methods in Medical Research, 2003
We present a simple approach to the analysis of fMRI data collected from several runs, sessions and subjects. We take advantage of the spatial nature of the data to reduce the noise in certain key parameters, achieving an increase in degrees of freedom for a mixed effects analysis.
openaire   +3 more sources

Active Data: Supporting the Grid Data Life Cycle

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07), 2007
Scientific applications often involve computation intensive workflows and may generate large amount of derived data. In this paper we consider a life cycle, which starts when the data is first generated, and tracks its progress through replication, distribution, deletion and possible re-computation.
Tim Ho, David Abramson 0001
openaire   +2 more sources

On Making Data Warehouses Active

2000
Data warehouses, which are the core elements of On-Line Analytical Processing (OLAP) systems, are passive since all tasks related to analyzing and making decisions must be carried out manually. This paper introduces a novel architecture, the active data warehouse, which applies the idea of event-condition-action rules (ECA rules) from active database ...
Michael Schrefl, Thomas Thalhammer
openaire   +2 more sources

Active Learning With Drifting Streaming Data

IEEE Transactions on Neural Networks and Learning Systems, 2014
In learning to classify streaming data, obtaining true labels may require major effort and may incur excessive cost. Active learning focuses on carefully selecting as few labeled instances as possible for learning an accurate predictive model. Streaming data poses additional challenges for active learning, since the data distribution may change over ...
Indre Zliobaite, Albert Bifet, Bernhard Pfahringer, Geoffrey Holmes 0001   +3 more
openaire   +3 more sources

Data Siloing as Infrastructural Activism

Proceedings of the ACM on Human-Computer Interaction
The refugee support ecosystem in the U.S.-Mexico Borderplex is resource-scarce, dynamic, and transitional, requiring intensive information work. To address coordination challenges among the cross-sector sociotechnical community working at one of the largest ports of entry for asylum seekers, the county government of El Paso, TX, USA, has proposed a ...
Shiva Darian, Fujiko Robledo Yamamoto, Amy Voida   +2 more
openaire   +2 more sources

Data Centre Activisms

Abstract This chapter deals with the growing numbers of local contestations of data centres spurred on by issues to do with noise pollution, pollution of water ways, and other energy deficits that have negatively affected local communities.
openaire   +2 more sources

Institutional Investor Activism and Employee Safety: The Role of Activist and Board Political Ideology

Organization Science, 2022
Philipp Meyer-Doyle, Wei Shi
exaly  

Climate activism and its effects

Wiley Interdisciplinary Reviews: Climate Change, 2021
Dana R. Fisher, Sohana Nasrin
exaly  

Woke brand activism authenticity or the lack of it

Journal of Business Research, 2022
Abas Mirzaei, Helen Siuki
exaly