10 citations · 31 across the 6 of their papers we have counts for
7 papers
Machine Learning-Powered Combinatorial Clock Auction
Ermis Soumalias, Jakob Weissteiner, Jakob Heiss +1
We study the design of iterative combinatorial auctions (ICAs). The main challenge in this domain is that the bundle space grows exponentially in the number of items. To address th…
Machine Learning-Powered Course Allocation
Ermis Soumalias, Behnoosh Zamanlooy, Jakob Weissteiner +1
We study the course allocation problem, where universities assign course schedules to students. The current state-of-the-art mechanism, Course Match, has one major shortcoming: stu…
Bayesian Optimization-based Combinatorial Assignment
Jakob Weissteiner, Jakob Heiss, Julien Siems +1
We study the combinatorial assignment domain, which includes combinatorial auctions and course allocation. The main challenge in this domain is that the bundle space grows exponent…
Monotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment
Jakob Weissteiner, Jakob Heiss, Julien Siems +1
Many important resource allocation problems involve the combinatorial assignment of items, e.g., auctions or course allocation. Because the bundle space grows exponentially in the…
NOMU: Neural Optimization-based Model Uncertainty
Jakob Heiss, Jakob Weissteiner, Hanna Wutte +2
We study methods for estimating model uncertainty for neural networks (NNs) in regression. To isolate the effect of model uncertainty, we focus on a noiseless setting with scarce t…
Fourier Analysis-based Iterative Combinatorial Auctions
Jakob Weissteiner, Chris Wendler, Sven Seuken +2
Recent advances in Fourier analysis have brought new tools to efficiently represent and learn set functions. In this paper, we bring the power of Fourier analysis to the design of…