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researcher

Gegi Thomas

9 papers hereh-index 8312 citations15 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author7
  • last author2

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.AI3
  • cs.LG3
  • cs.DC2
  • cs.CR1

identity via Semantic Scholar / OpenAlex

activity
20192026
most citedIBM Federated Learning: an Enterprise Framework White Paper V0.1

112 citations · 119 across the 8 of their papers we have counts for

collaborators
Showing 2020Show all

2 papers · 1 filter

cs.CR2020

MYSTIKO : : Cloud-Mediated, Private, Federated Gradient Descent

K. R. Jayaram, Archit Verma, Ashish Verma +2

Federated learning enables multiple, distributed participants (potentially on different clouds) to collaborate and train machine/deep learning models by sharing parameters/gradient…

cs.LG2020★ 112 cited

IBM Federated Learning: an Enterprise Framework White Paper V0.1

Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas +21

Federated Learning (FL) is an approach to conduct machine learning without centralizing training data in a single place, for reasons of privacy, confidentiality or data volume. How…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.