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Found 2 papers, 1 papers with code
FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning
In this paper, we propose FALCON, a novel combinatorial-optimization-based framework for network pruning that jointly takes into account model accuracy (fidelity), FLOPs, and sparsity constraints.
Fast as CHITA: Neural Network Pruning with Combinatorial Optimization
Our approach, CHITA, extends the classical Optimal Brain Surgeon framework and results in significant improvements in speed, memory, and performance over existing optimization-based approaches for network pruning.
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