Aditya Nagarsekar
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2026
Breaking chains with trees: Deep learning with $\mathcal{O}(\log N)$ parallel time complexity
This paper proposes Hierarchical Block-Local Learning (HBLL), a framework for training deep neural networks without full end-to-end backpropagation, achieving $\mathcal{O}(\log N)$ parallel time complexity.
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