Parameter Disentanglement for Diverse Representations
Recent advances in neural network architectures reveal the importance of diverse representations. However, simply integrating more branches or increasing the width for the diversity would inevitably increase model complexity, leading to prohibitive inference costs. In this paper, we revisit the lear...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2025-05-01
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| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2024.9020087 |
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