✨mHC-lite: You Don't Need 20 Sinkhorn-Knopp Iterations
📝 Summary:
mHC-lite proposes a novel reparameterization for Hyper-Connections, explicitly constructing exactly doubly stochastic matrices via convex combinations of permutations. This approach guarantees stability, improves training throughput with native operations, and outperforms prior methods.
🔹 Publication Date: Published on Jan 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05732
• PDF: https://arxiv.org/pdf/2601.05732
• Github: https://github.com/FFTYYY/mhc-lite
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For more data science resources:
✓ https://t.me/DataScienceT
#DeepLearning #MachineLearning #Optimization #Algorithm #AI
📝 Summary:
mHC-lite proposes a novel reparameterization for Hyper-Connections, explicitly constructing exactly doubly stochastic matrices via convex combinations of permutations. This approach guarantees stability, improves training throughput with native operations, and outperforms prior methods.
🔹 Publication Date: Published on Jan 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05732
• PDF: https://arxiv.org/pdf/2601.05732
• Github: https://github.com/FFTYYY/mhc-lite
==================================
For more data science resources:
✓ https://t.me/DataScienceT
#DeepLearning #MachineLearning #Optimization #Algorithm #AI
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