3 papers
cs.LG2026
Neural Network Approximation: A View from Polytope Decomposition
ZeYu Li, ShiJun Zhang, TieYong Zeng +1
Universal approximation theory offers a foundational framework to verify neural network expressiveness, enabling principled utilization in real-world applications. However, most ex…
cs.LG2025
NeuronSeek: On Stability and Expressivity of Task-driven Neurons
Hanyu Pei, Jing-Xiao Liao, Qibin Zhao +4
Drawing inspiration from our human brain that designs different neurons for different tasks, recent advances in deep learning have explored modifying a network's neurons to develop…
cs.LG2024
Hyper-Compression: Model Compression via Hyperfunction
Fenglei Fan, Juntong Fan, Dayang Wang +5
The rapid growth of large models' size has far outpaced that of computing resources. To bridge this gap, encouraged by the parsimonious relationship between genotype and phenotype…