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not only improve performance but also reduce the environmental footprint of distributed computing systems. By working on SmartScaleSys (S3), students will contribute to the future of sustainable and
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involve a lot of experiments using DL/AI methods. We will use the Monash <b>High</b> <b>Performance</b> <b>Computing</b> platform (MASSIVE) to do the experiments. Required knowledge You must have experience in Deep Learning, and have strong programming skills. Learn more about minimum entry...
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computing strategies, this project focuses on deploying ML models on real-world distributed infrastructures, improving system performance, scalability, and efficiency by optimizing resource usage (e.g
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Convolutional Neural Networks", ICML 2021 - "Privacy-Preserving Feature Selection with Secure Multiparty Computation", ICML 2021 - "High Performance Logistic Regression for Privacy-Preserving Genome
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Convolutional Neural Networks", ICML 2021 - "Privacy-Preserving Feature Selection with Secure Multiparty Computation", ICML 2021 - "High Performance Logistic Regression for Privacy-Preserving Genome
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angle, this project aims to build self-aware neural networks that are constructed in a way that is inspired by what we know about self-awareness circuits in the brain and the field of self-aware computing
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angle, this project aims to build self-aware neural networks that are constructed in a way that is inspired by what we know about self-awareness circuits in the brain and the field of self-aware computing
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ensembles of diverse opponents.” Neural Computing and Applications (2025). https://doi.org/10.1007/s00521-024-10511-9 de Arruda, H. F., Gracia-Lázaro, C., Aleta, A. and Moreno, Y. “Collective
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ensembles of diverse opponents.” Neural Computing and Applications (2025). https://doi.org/10.1007/s00521-024-10511-9 de Arruda, H. F., Gracia-Lázaro, C., Aleta, A. and Moreno, Y. “Collective
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applicable computing discipline should contact me by email at [email protected]. Curriculum vitae, references and an academic transcript of results are to be presented on request. For PhD applicants