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A. Menon

53 papers hereh-index 4411.1k citations124 works total

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

author position
  • first author6
  • middle author41
  • last author5

Across the 52 of 53 papers where every author was matched, so the position is known.

fields
  • cs.LG36
  • cs.CL9
  • cs.IR4
  • stat.ML2
  • cs.AI1
  • cs.HC1
same name
  • A. Menon — 13 papers, h 19
  • A. Menon — 10 papers, h 13
  • A. Menon — 9 papers, h 5
  • A. Menon — 9 papers, h 7
  • A. Menon — 6 papers, h 3
  • A. Menon — 4 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20122025
most citedFederated Learning with Only Positive Labels

40 citations · 177 across the 37 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.LG2019

Online Hierarchical Clustering Approximations

Aditya Krishna Menon, Anand Rajagopalan, Baris Sumengen +3

Hierarchical clustering is a widely used approach for clustering datasets at multiple levels of granularity. Despite its popularity, existing algorithms such as hierarchical agglom…

cs.LG2019★ 24 cited

Fairness risk measures

Robert C. Williamson, Aditya Krishna Menon

Ensuring that classifiers are non-discriminatory or fair with respect to a sensitive feature (e.g., race or gender) is a topical problem. Progress in this task requires fixing a de…

cs.IR2019

Cold-start Playlist Recommendation with Multitask Learning

Dawei Chen, Cheng Soon Ong, Aditya Krishna Menon

Playlist recommendation involves producing a set of songs that a user might enjoy. We investigate this problem in three cold-start scenarios: (i) cold playlists, where we recommend…

cs.LG2019

Noise-tolerant fair classification

Alexandre Louis Lamy, Ziyuan Zhong, Aditya Krishna Menon +1

Fairness-aware learning involves designing algorithms that do not discriminate with respect to some sensitive feature (e.g., race or gender). Existing work on the problem operates…

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