270 learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Monash University
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Current federated learning architectures in mobile healthcare are limited to a centralised model without considering the full continuum of mobile-edge-cloud. Additionally, to support different data
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Background and Motivation Modern deep learning models have achieved remarkable success in computer vision and natural language processing. However, they typically produce overconfident predictions
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model with each SNP independently, perhaps adjusting for other covariates such as age and sex. This project will focus on developing and applying novel machine learning and AI methods to improve
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financial, personal, and confidential information. This project seeks to introduce machine learning and artificial intelligence techniques to effectively detect phishing websites. By leveraging these advanced
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Machine Learning without Centralized Training Data”, https://ai.googleblog.com/2017/04/federated-learning-collaborative.html [2] “Learning with Privacy at Scale”, https://machinelearning.apple.com/research
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mechanical loading of such samples. The focus of the PhD project will be to use machine learning techniques to better understand the interplay between the crystal orientations and deformation patterns in a
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This research project aims to address the critical need for privacy-enhancing techniques in machine learning (ML) applications, particularly in scenarios involving sensitive or confidential data
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This PhD project aims to mitigate the data scarcity of new NLP and Multimodal applications by developing novel active learning algorithms. In this project, the student will leverage large foundation
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Over the past decades, we have witnessed the emergence and rapid development of deep learning. DL has been successfully deployed in many real-life applications, including face recognition, automatic
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warming. The bot will support students' self-regulated learning skills which were theorised to promote learning achievements and boost motivation. This research will unfold over the following 3 phases: 1