Romain Chor

Papers & Preprints

Google Scholar profile

• Heterogeneity Matters Even More in Distributed Learning: Study from Generalization Perspective.
  M. Kavian, R. Chor, M. Sefidgaran and A. Zaidi. Under review by Neural Information Processing Systems 39 (NeurIPS), May 2025. Link.

• Generalization Error of Federated Learning & Clients-Server Communication: Bounds, Algorithms for their Computation and Implications.
  R. Chor, A. Zaidi and M. Sefidgaran. Under review by IEEE Transactions on Information Theory, March 2025.

• Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often!
  M. Sefidgaran, R. Chor, A. Zaidi and Y. Wan. Accepted at Forty-first International Conference on Machine Learning (ICML), 2024. Link. 

• More Communication Does Not Result in Smaller Generalization Error in Federated Learning. 
  R. Chor, M. Sefidgaran and A. Zaidi. International Symposium on Information Theory (ISIT), 2023. Link. 

• Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning.
  M. Sefidgaran, R. Chor and A. Zaidi. Neural Information Processing Systems 35 (NeurIPS), 2022. Link. 

Other research activities

• I am currently preparing a monograph paper on the topic of distributed learning algorithms & their generalization analysis, with several co-authors.
  The paper will be available end of 2025.

• I have had the opportunity to serve as a reviewer for the following conferences and journals:
  NeurIPS 2024, AIStats 2025, ICML 2025, ECAI 2025, IEEE Transactions on Information Theory

• Probability theory (~26h)
  Fall 2024. École supérieure d’ingénieurs en électrotechnique et électronique (ESIEE Paris)

• Statistics (~16h)
  Fall 2023 and Fall 2024. École supérieure d’ingénieurs en électrotechnique et électronique (ESIEE Paris).

• Coding theory (~26h)
  Fall 2023. École supérieure d’ingénieurs en électrotechnique et électronique (ESIEE Paris).

• Ph.D. student in Statistical Learning
  2022 - Today. Huawei Paris Research Center (Huawei Technologies France) and Laboratoire d'Informatique Gaspard Monge (Université Gustave Eiffel).

• Research engineer in Statistical Learning
  Nov.-Dec. 2019. Laboratoire d'Informatique Gaspard Monge (Université Gustave Eiffel).

• Data Scientist Intern
  2020. Safety Line, Paris.

• M.Sc. in Statistics.
  2019 - 2020. Sorbonne Université, Paris.

• France Information Theory PhD Workshop, June 2024. Palaiseau, France.
  Oral presentation of my PhD work and some recent results at Telecom Paris. Link 

• International Symposium on Information Theory (ISIT), July 2023. Taipei, Taiwan.
  Oral presentation of published paper "More Communication Does Not Result in Smaller Generalization Error in Federated Learning". 

• London Symposium on Information Theory, 2023. May 2023. London, United Kingdom.
  Poster presentation.

• "NeurIPS in Paris". December 2022. Paris, France.
  Poster presentation of published paper at NeurIPS 2022 conference "Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning".