Robust PAC$^m$: Training Ensemble Models Under Misspecification and Outliers-Reference-Cited by-同舟云学术

Robust PAC$^m$: Training Ensemble Models Under Misspecification and Outliers

Author:

Zecchin Matteo¹^ORCID,Park Sangwoo¹^ORCID,Simeone Osvaldo¹^ORCID,Kountouris Marios²,Gesbert David²

Affiliation:

1. Department of Engineering, King’s Communications, Learning and Information Processing (KCLIP) Laboratory, King’s College London, London, U.K.

2. Communication Systems Department, EURECOM, Sophia Antipolis, France

Funder

Marie Curie Action WINDMILL

European Union’s Horizon Europe Project CENTRIC

European Research Council (ERC) through the European Union’s Horizon 2020 Research and Innovation Program

ERC through the European Union’s Horizon 2020 Research and Innovation Program

Open Fellowship of the Engineering and Physical Sciences Research Council

Agence Nationale de la Recherche (ANR) through the 3IA Artificial Intelligence Interdisciplinary Project French

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

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4. Calibrating AI Models for Wireless Communications via Conformal Prediction;IEEE Transactions on Machine Learning in Communications and Networking;2023