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Umang Aggarwal

4 papers hereh-index 4136 citations10 works total

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

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.LG2

identity via Semantic Scholar / OpenAlex

most citedMinority Class Oriented Active Learning for Imbalanced Datasets

14 citations · 19 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2022★ 14 cited

Minority Class Oriented Active Learning for Imbalanced Datasets

Umang Aggarwal, Adrian Popescu, Céline Hudelot

Active learning aims to optimize the dataset annotation process when resources are constrained. Most existing methods are designed for balanced datasets. Their practical applicabil…

cs.LG2022★ 5 cited

A Comparative Study of Calibration Methods for Imbalanced Class Incremental Learning

Umang Aggarwal, Adrian Popescu, Eden Belouadah +1

Deep learning approaches are successful in a wide range of AI problems and in particular for visual recognition tasks. However, there are still open problems among which is the cap…

cs.CV2022

Optimizing Active Learning for Low Annotation Budgets

Umang Aggarwal, Adrian Popescu, Céline Hudelot

When we can not assume a large amount of annotated data , active learning is a good strategy. It consists in learning a model on a small amount of annotated data (annotation budget…

cs.CV2020

Active Class Incremental Learning for Imbalanced Datasets

Eden Belouadah, Adrian Popescu, Umang Aggarwal +1

Incremental Learning (IL) allows AI systems to adapt to streamed data. Most existing algorithms make two strong hypotheses which reduce the realism of the incremental scenario: (1)…

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