7 citations · 23 across the 14 of their papers we have counts for
3 papers · 1 filter
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…
Extending Path-Dependent NJ-ODEs to Noisy Observations and a Dependent Observation Framework
William Andersson, Jakob Heiss, Florian Krach +1
The Path-Dependent Neural Jump Ordinary Differential Equation (PD-NJ-ODE) is a model for predicting continuous-time stochastic processes with irregular and incomplete observations.…
How (Implicit) Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part II: the Multi-D Case of Two Layers with Random First Layer
Jakob Heiss, Josef Teichmann, Hanna Wutte
Randomized neural networks (randomized NNs), where only the terminal layer's weights are optimized constitute a powerful model class to reduce computational time in training the ne…