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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.
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campus Time Commitment: Up to 10 meetings per year; 3-5 hours per meeting, plus additional time for pre-reading Contact:animal.ethics@monash.edu Monash University’s School of Biological Sciences Animal
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-term appointment Remuneration: The successful applicant will receive a tax-free stipend, at the current value of $36,063 per annum 2025 full-time rate, as per the Monash Research Training Program (RTP
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We are excited to offer a fully funded PhD position at the Faculty of Engineering, Monash University (Australia). This project focuses on developing new algorithms to equip social robots with
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This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and their uncertainty to different stakeholders, and evaluate the effect of the...
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largely opaque to computational analysis, into a transparent phenomenon from which selected features can be captured and rendered visible for the purposes of professional development for teachers. Depending
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Dr Aunty Doris Paton Indigenous Accommodation Scholarship The Faculty of Medicine, Nursing and Health Sciences is offering the Dr Aunty Doris Paton Scholarship for Indigenous Students to support
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the Monash Research Training Program (RTP) Stipend www.monash.edu/study/fees-scholarships/scholarships/find-a-scholarship/research-training-program-scholarship#scholarship-details Be inspired, every day Drive
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In recent years, the rise in cybercrimes has significantly increased the vulnerability of the open internet to various threats and cyber-attacks. Among these, phishing stands out as one of the most perilous crimes worldwide. In a phishing attack, perpetrators create fraudulent websites that...
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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals from mobile devices and classify them into different categories or types of ringtones. The...