University Guest Lectures

by IBM Academic Ambassadors

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Found 2 results


Fairness, Explainability & Robustness in Machine Learning

Recent years have seen an overwhelming body of work on fairness and bias in Machine Learning (ML) models. This is not unexpected, as fairness is a complex and multi-faceted concept that depends on context and culture. Particularly in machine learning, …


Towards clinical relevance: Predictive modeling applied to brain imaging

The application of machine learning methods to the increasingly larger observational studies of neurological and psychiatric disorders provides the opportunity of generating individualized assessments for people with a given condition, while also enabling the detection of brain correlates of disease. …