About this document
Sequentialattention++ For Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization by d.alistarh is a document available to read on EtoBox.
The document presents SequentialAttention++, a novel framework that combines differentiable pruning and combinatorial optimization for structured neural network pruning, specifically focusing on block sparsification. The authors provide theoretical insights into differentiable pruning techniques, showing their equivalence to nonconvex regularization methods and establishing the uniqueness of sparse global minima. Empirically, the proposed algorithm demonstrates significant advancements in block-wise pruning
- Author
- d.alistarh
- Language
- EN