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Demo Data from SIGIR 2026 / reviewers in the wild / expert

Emilio Luz-Ricca

dblp:350/3977 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-4180-4123ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Efficient and distributed learning · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Efficient and distributed learning › federated learning
data heterogeneity		 0.712023
Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity · ICLR 2023
Machine learning › Efficient and distributed learning
federated learning		 0.712023
Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity · ICLR 2023
Machine learning › Efficient and distributed learning › federated learning › communication-efficient federated learning
one-shot federated learning		 0.712023
Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity · ICLR 2023

Methods — techniques the papers use, named apart from their topics

data-free learning · 0.7
YearPublicationVenuePosition
2023 Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity
Clare Elizabeth Heinbaugh, Emilio Luz-Ricca, Huajie Shao
 ICLR2