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Hadi Ghauch

2 accepted papers

2026

Learning High-Dimensional Parity Functions with Product Networks using Gradient Descent

ICML 2026poster

Parity functions are fundamental Boolean operations with critical applications across machine learning, cryptography, and error correction. Yet, learning high-dimensional parity functions poses significant challenges: in a general setting, standard neural network architectures typically require expo…

Cited by 0SourceScholar
2019

Learning and Data Selection in Big Datasets

ICML 2019oral

Finding a dataset of minimal cardinality to characterize the optimal parameters of a model is of paramount importance in machine learning and distributed optimization over a network. This paper investigates the compressibility of large datasets. More specifically, we propose a framework that jointly…

Cited by 17SourcePDFScholar