SequentialAttention+ + for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization
–Neural Information Processing Systems
Pruning methods for neural networks [LeCun et al., 1989] replace dense weight matrices by sparse
Neural Information Processing Systems
Feb-16-2026, 09:30:03 GMT
- Country:
- Africa > Rwanda
- Asia
- Singapore (0.04)
- South Korea > Seoul
- Seoul (0.04)
- Europe
- North America
- Canada
- British Columbia > Vancouver (0.04)
- Ontario > National Capital Region
- Ottawa (0.04)
- Quebec > Montreal (0.04)
- United States
- California
- Alameda County > Berkeley (0.04)
- Los Angeles County > Long Beach (0.04)
- San Francisco County > San Francisco (0.14)
- Colorado > Denver County
- Denver (0.04)
- Hawaii > Honolulu County
- Honolulu (0.04)
- Louisiana > Orleans Parish
- New Orleans (0.04)
- California
- Canada
- Genre:
- Research Report > Experimental Study (1.00)
- Industry:
- Information Technology (0.46)
- Technology:
- Information Technology > Artificial Intelligence
- Machine Learning > Neural Networks (1.00)
- Representation & Reasoning > Search (1.00)
- Vision (0.93)
- Information Technology > Artificial Intelligence