In the standard use case of Algorithmic Fairness, the goal is to elimina...
Algorithmic Fairness and the explainability of potentially unfair outcom...
In supervised learning, it is quite frequent to be confronted with real
...
The insurance industry is heavily reliant on predictions of risks based ...
Algorithmic Fairness is an established field in machine learning that ai...
In this work, we consider the problem of imbalanced data in a regression...
This paper designs a sequential repeated game of a micro-founded society...
Since the beginning of their history, insurers have been known to use da...
At the core of insurance business lies classification between risky and
...
The economic consequences of drought episodes are increasingly important...
Boosting techniques and neural networks are particularly effective machi...
Family history is usually seen as a significant factor insurance compani...
Reinforcement learning algorithms describe how an agent can learn an opt...
The Pareto model is very popular in risk management, since simple analyt...
This article presents a set of tools for the modeling of a spatial alloc...
Recently, Alderson et al. (2009) mentioned that (strict) Scale-Free netw...
The well-known generalized estimating equations (GEE) is widely used to
...