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2. Ravensport: How much warning can ML give before a cyberattack? Can an agent mitigate attacks without disrupting operations? Participants monitor and defend a realistic infrastructure as multi-stage attacks unfold. github.com/alan-turing-...
#SaTML2027 also has four workshops: 1. New AdvML-Frontiers: Human Centered Trustworthy Machine Learning. Focused on understanding which risks lead to real-world harm or which protections are truly needed. advml-frontier.github.io/satml2027/
2. MIRROR: Meta-science in AI Security Research. How can our community conduct more reliable & reproducible research? Looking in 3 dir: backwards (where past research goes wrong), forwards (good research practices), inwards (how do LLMs affect research?) mirror-workshop.io
3. WICE: Workshop on Incentives and Contribution Evaluation. Exploring contribution evaluation and incentives in collaborative learning settings. wice-satml.github.io
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4. TrustTFM: Trustworthiness of Tabular Foundation Models (TFMs). Tabular data is ubiquitous, and regulations make trustworthiness essential: robustness, security, privacy, explainability, fairness, and compliance risks. karimtito.github.io/trusttfm-2027/
More details on the website: satml.org/competitions/ satml.org/workshops/ Please check them out! We look forward to your participation in the competitions, workshops, and the main program itself.