Corruptions of Supervised Learning Problems: Typology and Mitigations
Iacovissi, Laura, Nan Lu, and Robert C. Williamson. 2024. “Corruptions of Supervised Learning Problems: Typology and Mitigations”. ArXiv.
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Slow Science
Machine learning research is notoriously fast paced. Can one get off the treadmill and embrace a notion of slow science? I am pleased to be able to argue yes by example! Recently I have had two works published with a very long gestation. The first Geometry and Calculus of Losses reports work that...
Limits to Predicting Online Speech Using Large Language Models
Remeli, Mina, Moritz Hardt, and Robert C. Williamson. 2024. “Limits to Predicting Online Speech Using Large Language Models”. ArXiv.
Four Facets of Forecast Felicity: Calibration, Predictiveness, Randomness and Regret
Derr, Rabanus, and Robert C. Williamson. 2024. “Four Facets of Forecast Felicity: Calibration, Predictiveness, Randomness and Regret.”
Teaching
Thesis Projects (Bachelor and Masters) See the thesis project page. ( Summer 2025) Bridging Theory and Practice: Reliable ML in Data Corruption Scenarios This is a Master-level seminar focused on reliable machine learning under data corruption, combining theory and practice in areas such as medicine...