Exploring Machine Learning Needs Mathematical Optimization With Prof Paula Brito
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- Abstract: Adversarial
- Abstract: Counterfactual explanations are usually generated through heuristics that are sensitive to the search's initial conditions.
- Abstract: Advances in
- Machine Learning NeEDS Mathematical Optimization
- Abstract: In this talk we initially analyze null hypothesis statistical testing, the use of p-values and the controversy around them.
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Abstract: In classical Statistics and Multivariate Data Analysis data is usually represented in a data array where each row ... Abstract: The talk focuses on block coordinate decomposition methods when optimizating a finite sum of functions. Specifically, we ... Title: Tactical Planning under Imperfect Information: A Fast Matheuristic for Two-Stage Stochastic Programs Through Supervised ... Abstract: Special paediatric intensive care retrieval teams (PICRTs), based in 11 locations across England and Wales, have been ...
Abstract: Discussions about trustworthy and responsible AI have become central across multiple communities in recent years ...
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