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ADM+S Thesis Bootcamp

The Oxford Scholar 427 Swanston Street, Melbourne, VIC
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Registrations are open for the ADM+S Thesis Boot Camp. Designed for students in mid-to-late candidature with a significant amount of data collected, the program aims to re-energise students’ writing progress and overcome hurdles slowing them down. This program will include focused discussion on approaches to writing, thesis structure, clarifying arguments, and strategies for writing quickly and writing well. Thesis Boot Camp participants will work through common challenges faced at this point in the journey, such as writer’s block and thesis fatigue, to achieve significant progress on their manuscript. The bootcamp will be delivered by Dr Liam Connell.


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ADM+S Members Only. Beyond XAI: Explainable Data-driven Modelling for Human Reasoning and Decision Support

Beyond XAI: Explainable Data-driven Modelling for Human Reasoning and Decision Support

ADM+S Centre, RMIT University 106-108 Victoria Street, Carlton, VIC
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Join this session delivered by ADM+S Affiliate Kacper Sokol and Associate Investigator Danula Hetticachchi as they explore how we can reimagine XAI by drawing upon a broad range of relevant interdisciplinary findings.


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Text: ADM+S Members only. Practical Machine Learning Explainability. Image: Traditional Tibetan weaver in Dharamsala India working at a loom, framed by yellow bounding boxes that classify different elements of textile craft. The image features digital distortion effects and fragmented views of weaving tools and finished textiles. Text has been selectively blanched from the composition, symbolizing whose voices are included or excluded in conversations about digital transformation.

Practical Machine Learning Explainability: Surrogate Explainers and Fairwashing

ADM+S Centre, RMIT University 106-108 Victoria Street, Carlton, VIC
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Join this session delivered by ADM+S Affiliate Kacper Sokol and Associate Investigator Danula Hetticachchi as they introduce the three core components of surrogate explainers: data sampling, interpretable representation and explanation generation in view of text, image and tabular data.


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