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20192023
most citedOptimising Individual-Treatment-Effect Using Bandits

3 citations · 4 across the 5 of their papers we have counts for

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cs.LG2023

A Causal Perspective on Loan Pricing: Investigating the Impacts of Selection Bias on Identifying Bid-Response Functions

Christopher Bockel-Rickermann, Sam Verboven, Tim Verdonck +1

In lending, where prices are specific to both customers and products, having a well-functioning personalized pricing policy in place is essential to effective business making. Typi…

cs.LG2023

Sample-Level Weighting for Multi-Task Learning with Auxiliary Tasks

Emilie Grégoire, Hafeez Chaudhary, Sam Verboven

Multi-task learning (MTL) can improve the generalization performance of neural networks by sharing representations with related tasks. Nonetheless, MTL can also degrade performance…

cs.LG2020★ 1 cited

HydaLearn: Highly Dynamic Task Weighting for Multi-task Learning with Auxiliary Tasks

Sam Verboven, Muhammad Hafeez Chaudhary, Jeroen Berrevoets +1

Multi-task learning (MTL) can improve performance on a task by sharing representations with one or more related auxiliary-tasks. Usually, MTL-networks are trained on a composite lo…

cs.LG2020

Autoencoders for strategic decision support

Sam Verboven, Jeroen Berrevoets, Chris Wuytens +2

In the majority of executive domains, a notion of normality is involved in most strategic decisions. However, few data-driven tools that support strategic decision-making are avail…

cs.LG2019★ 3 cited

Optimising Individual-Treatment-Effect Using Bandits

Jeroen Berrevoets, Sam Verboven, Wouter Verbeke

Applying causal inference models in areas such as economics, healthcare and marketing receives great interest from the machine learning community. In particular, estimating the ind…