no code implementations • NeurIPS 2021 • Borja Rodríguez-Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund
This work presents several expected generalization error bounds based on the Wasserstein distance.
no code implementations • 23 Nov 2020 • Sina Molavipour, Germán Bassi, Mladen Čičić, Mikael Skoglund, Karl Henrik Johansson
In an intelligent transportation system, the effects and relations of traffic flow at different points in a network are valuable features which can be exploited for control system design and traffic forecasting.
no code implementations • 21 Oct 2020 • Borja Rodríguez-Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund
In this work, we unify several expected generalization error bounds based on random subsets using the framework developed by Hellstr\"om and Durisi [1].
1 code implementation • 12 Jun 2020 • Sina Molavipour, Germán Bassi, Mikael Skoglund
The estimation of mutual information (MI) or conditional mutual information (CMI) from a set of samples is a long-standing problem.
no code implementations • 12 May 2020 • Borja Rodríguez-Gálvez, Germán Bassi, Mikael Skoglund
In this work, we study the generalization capability of algorithms from an information-theoretic perspective.
no code implementations • 6 Nov 2019 • Sina Molavipour, Germán Bassi, Mikael Skoglund
Several recent works in communication systems have proposed to leverage the power of neural networks in the design of encoders and decoders.
