3 citations · 5 across the 3 of their papers we have counts for
7 papers · 1 filter
Testing for directed information graphs
Sina Molavipour, Germán Bassi, Mikael Skoglund
In this paper, we study a hypothesis test to determine the underlying directed graph structure of nodes in a network, where the nodes represent random processes and the direction o…
On Random Subset Generalization Error Bounds and the Stochastic Gradient Langevin Dynamics Algorithm
Borja Rodríguez-Gálvez, Germán Bassi, Ragnar Thobaben +1
In this work, we unify several expected generalization error bounds based on random subsets using the framework developed by Hellström and Durisi [1]. First, we recover the bounds…
Secure Strong Coordination
Giulia Cervia, German Bassi, Mikael Skoglund
We consider a network of two nodes separated by a noisy channel, in which the source and its reconstruction have to be strongly coordinated, while simultaneously satisfying the str…
Neural Estimators for Conditional Mutual Information Using Nearest Neighbors Sampling
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. A recent line of work in this area has leveraged…
Upper Bounds on the Generalization Error of Private Algorithms for Discrete Data
Borja Rodríguez-Gálvez, Germán Bassi, Mikael Skoglund
In this work, we study the generalization capability of algorithms from an information-theoretic perspective. It has been shown that the expected generalization error of an algorit…
Conditional Mutual Information Neural Estimator
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. In this approach, these blocks can be t…