research
∙
05/18/2023
Mode Connectivity in Auction Design
Optimal auction design is a fundamental problem in algorithmic game theo...
share
research
∙
03/29/2023
Training Neural Networks is NP-Hard in Fixed Dimension
We study the parameterized complexity of training two-layer neural netwo...
research
∙
02/24/2023
Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes
We prove that the set of functions representable by ReLU neural networks...
research
∙
04/04/2022
Training Fully Connected Neural Networks is ∃ℝ-Complete
We consider the algorithmic problem of finding the optimal weights and b...
research
∙
05/31/2021
Towards Lower Bounds on the Depth of ReLU Neural Networks
We contribute to a better understanding of the class of functions that i...
research
∙
05/18/2021
The Computational Complexity of ReLU Network Training Parameterized by Data Dimensionality
Understanding the computational complexity of training simple neural net...
research
∙
02/12/2021
ReLU Neural Networks for Exact Maximum Flow Computation
Understanding the great empirical success of artificial neural networks ...
research
∙
08/21/2020
Coloring Drawings of Graphs
We consider face-colorings of drawings of graphs in the plane. Given a m...
research
∙
05/28/2020
Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size
In view of the undisputed success of neural networks and due to the rema...
research
∙
01/09/2019