511 citations · 1.2k across the 54 of their papers we have counts for
6 papers · 1 filter
On the Role of Reversible Instance Normalization
Gaspard Berthelier, Tahar Nabil, Etienne Le Naour +3
Data normalization is a crucial component of deep learning models, yet its role in time series forecasting remains insufficiently understood. In this paper, we identify three centr…
The Method of Gaps: Exact Expressions for the Generalization Error of Supervised Learning Algorithms
Samir M. Perlaza, Xinying Zou
In this paper, the method of gaps, a technique for deriving closed-form expressions in terms of information measures for the generalization error of supervised learning algorithms,…
Generalization Analysis of Machine Learning Algorithms via the Worst-Case Data-Generating Probability Measure
Xinying Zou, Samir M. Perlaza, Iñaki Esnaola +1
In this paper, the worst-case probability measure over the data is introduced as a tool for characterizing the generalization capabilities of machine learning algorithms. More spec…
On the Validation of Gibbs Algorithms: Training Datasets, Test Datasets and their Aggregation
Samir M. Perlaza, Iñaki Esnaola, Gaetan Bisson +1
The dependence on training data of the Gibbs algorithm (GA) is analytically characterized. By adopting the expected empirical risk as the performance metric, the sensitivity of the…
Empirical Risk Minimization with Relative Entropy Regularization: Optimality and Sensitivity Analysis
Samir M. Perlaza, Gaetan Bisson, Iñaki Esnaola +2
The optimality and sensitivity of the empirical risk minimization problem with relative entropy regularization (ERM-RER) are investigated for the case in which the reference is a s…
Learning Equilibria with Partial Information in Decentralized Wireless Networks
Luca Rose, Samir M. Perlaza, Samson Lasaulce +1
In this article, a survey of several important equilibrium concepts for decentralized networks is presented. The term decentralized is used here to refer to scenarios where decisio…