Unified Deep Discrete Representation Learning Framework
Discrete representation learning
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@misc{
vuong2024unified,
title={Unified Deep Discrete Representation Learning Framework},
author={Long Tung Vuong and Bang Giang Le and Vy Vo and Anh Tuan Bui and Viet Cuong Ta and Thanh-Toan Do and Dinh Phung and Trung Le},
year={2024},
url={https://openreview.net/forum?id=oioWoT0OSO}
}
Recent years have seen significant success of deep discrete representation learning across a broad range of domains. Existing frameworks typically operate on flat latents, overlooking the hierarchical structure within discrete latent spaces, which if effectively exploited could yield richer and more expressive representations. This work contributes a novel hierarchical discrete representation learning framework that flexibly generalizes to a variety of tasks and demonstrates effectiveness across diverse applications. We provide a theoretical analysis on sample complexity and additionally study the effect of codebook utilization on task performance. We offer practical insights into how these factors interplay in different learning scenarios.
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~Long_Tung_Vuong1 ~Bang_Giang_Le1 ~Vy_Vo2 ~Anh_Tuan_Bui2 ~Viet_Cuong_Ta2 ~Thanh-Toan_Do4 ~Dinh_Phung2 ~Trung_Le2
Long Tung Vuong Bang Giang Le Vy Vo Anh Tuan Bui Viet Cuong Ta Thanh-Toan Do Dinh Phung Trung Le
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Discrete representation learning
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vuong|unified_deep_discrete_representation_learning_framework
unsupervised, self-supervised, semi-supervised, and supervised representation learning
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Unified Deep Discrete Representation Learning Framework
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