7 citations · 23 across the 14 of their papers we have counts for
3 papers · 1 filter
How Infinitely Wide Neural Networks Can Benefit from Multi-task Learning -- an Exact Macroscopic Characterization
Jakob Heiss, Josef Teichmann, Hanna Wutte
In practice, multi-task learning (through learning features shared among tasks) is an essential property of deep neural networks (NNs). While infinite-width limits of NNs can provi…
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…