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20222026
most citedDeep Reinforcement Learning and Mean-Variance Strategies for Responsible Portfolio Optimization

1 citations · 1 across the 6 of their papers we have counts for

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cs.LG2022

Rethinking Log Odds: Linear Probability Modelling and Expert Advice in Interpretable Machine Learning

Danial Dervovic, Nicolas Marchesotti, Freddy Lecue +1

We introduce a family of interpretable machine learning models, with two broad additions: Linearised Additive Models (LAMs) which replace the ubiquitous logistic link function in G…

cs.LG2022

Towards learning to explain with concept bottleneck models: mitigating information leakage

Joshua Lockhart, Nicolas Marchesotti, Daniele Magazzeni +1

Concept bottleneck models perform classification by first predicting which of a list of human provided concepts are true about a datapoint. Then a downstream model uses these predi…