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Online learning of image classifiers with expanding labels

Published on:

28 August 2023

Primary Category:

Machine Learning

Paper Authors:

Byung Hyun Lee,

Okchul Jung,

Jonghyun Choi,

Se Young Chun

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Key Details

Proposes hierarchical label expansion (HLE), a new continual learning setup mirroring real-world knowledge accumulation

Introduces pseudo-labeling based memory management and flexible memory sampling for HLE

Demonstrates significant performance gains on HLE over prior CL methods

Shows strong results on HLE while still outperforming on existing CL setups

Provides comprehensive analysis and ablation studies validating contributions

AI generated summary

Online learning of image classifiers with expanding labels

This paper proposes a new continual learning setup called hierarchical label expansion that simulates real-world knowledge accumulation, where learning begins with coarse categories that expand into finer subcategories over time. The paper introduces a method to tackle this setup using pseudo-labeling, flexible memory sampling, and hierarchy-aware training.

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