Website
http://dataportal.arc.gov.au/NCGP/API/grants/DP140102270
Funding Status
Closed
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Funded Activity Summary
Online Learning for Large Scale Structured Data in Complex Situations. Online Learning (OL) is the process of predicting answers for a sequence of questions. OL has enjoyed much attention in recent years due to its natural ability of processing large scale non-structured data and adapting to a changing environment. However, OL has three weaknesses: it does not scale for structured data; it often assumes that all of the data are equally important; it often considers that all of the data are complete and noise-free. These weaknesses limit its utility, because real data such as those that must be analysed in processing social networks, fraud detection do not satisfy the restrictions. The aim of this project is to develop theoretical and practical advances in OL that overcome the existing weaknesses.Funded Activity Details
Start Date: 2014
End Date: 12-2018
Funding Scheme: Discovery Projects
Funding Amount: $380,787.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Pattern Recognition and Data Mining | Computer Vision | Artificial Intelligence and Image Processing
