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The Lingering of Gradients: How to Reuse Gradients Over Time
Zeyuan Allen-Zhu, David Simchi-Levi, Xinshang Wang
This is meaningful because in most applications, the time complexities for evaluating gradients at different points are of the same magnitude.
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Quadratic Decomposable Submodular Function Minimization
Pan Li, Niao He, Olgica Milenkovic
Neural Information Processing Systems http://nips.cc/
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Toward a Characterization of Loss Functions for Distribution Learning
Nika Haghtalab, Cameron Musco, Bo Waggoner
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fdb2c3bab9d0701c4a050a4d8d782c7f-Paper.pdf
The ability toleverage large-scale hardware parallelism has been one ofthe key enablers of the accelerated recent progress in machine learning.
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