30 citations · 33 across the 4 of their papers we have counts for
5 papers
Direct Profit Estimation Using Uplift Modeling under Clustered Network Interference
Bram van den Akker
Uplift modeling is a key technique for promotion optimization in recommender systems, but standard methods typically fail to account for interference, where treating one item affec…
Rethinking Knowledge Transfer in Learning Using Privileged Information
Danil Provodin, Bram van den Akker, Christina Katsimerou +2
In supervised machine learning, privileged information (PI) is information that is unavailable at inference, but is accessible during training time. Research on learning using priv…
Practical Bandits: An Industry Perspective
Bram van den Akker, Olivier Jeunen, Ying Li +3
The bandit paradigm provides a unified modeling framework for problems that require decision-making under uncertainty. Because many business metrics can be viewed as rewards (a.k.a…
Machine Learning for Fraud Detection in E-Commerce: A Research Agenda
Niek Tax, Kees Jan de Vries, Mathijs de Jong +5
Fraud detection and prevention play an important part in ensuring the sustained operation of any e-commerce business. Machine learning (ML) often plays an important role in these a…
ViTOR: Learning to Rank Webpages Based on Visual Features
Bram van den Akker, Ilya Markov, Maarten de Rijke
The visual appearance of a webpage carries valuable information about its quality and can be used to improve the performance of learning to rank (LTR). We introduce the Visual lear…