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On-device machine learning (ML) is rapidly gaining popularity on mobile devices. Mobile developers can use on-device ML to enable ML features at users’ mobile devices, such as face recognition
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would develop new computational methods for modelling Groupthink that can account for real-world complexity in agents’ behaviour, and build realistic enough models that can fit past and present empirical
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There are sometimes emerging prolonged periods of highly persistent evolution in time series. Share prices of successful start-ups, the number of confirmed cases in a pandemic (e.g., COVID-19
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will work as part of a larger research team on this project which includes multiple industry partners. The objective of the Actionable Data project is to develop and prove a reusable framework for
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Evolution. Please check our publications for more details: http://garciajulian.com [1] “Empirical Agent Based Models of Cooperation in Public Goods Games | Proceedings of the Fourteenth ACM Conference
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Despite the popularity of providing text analysis as a service by high-tech companies, it is still challenging to develop and deploy NLP applications involving sensitive and demographic information
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Queensland, my opportunities for attending university were limited due to my circumstances. The Achieving Potential Support Scholarship and Monash Relocation Grant has provided me financial assistance and
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DNA or RNA motif discovery is a popular biological method to identify over-represented DNA or RNA sequences in next generation sequencing experiments. These motifs represent the binding site of transcription factors or RNA-binding proteins. DNA or RNA binding sites are often variable. However,...
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Online fraud, also referred to as cyberscams, is increasingly becoming a cybersecurity problem that technical cybersecurity specialists are unable to effectively detect. Given the difficulty in the automatic detection of scams, the onus is often pushed back to humans to detect. Gamification and...
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The detection of human activities is crucial for effective monitoring purposes. The challenge lies in accurately and promptly identifying various types of activities from videos and images captured in diverse, real-world environments. Both classical machine learning methods and deep learning...