2 papers
cs.LG2026
Hardware-Friendly Input Expansion for Accelerating Function Approximation
Hu Lou, Yin-Jun Gao, Dong-Xiao Zhang +3
One-dimensional function approximation is a fundamental problem in scientific computing and engineering applications. While neural networks possess powerful universal approximation…
cs.LG2026
Phase-space entropy at acquisition reflects downstream learnability
Xiu-Cheng Wang, Jun-Jie Zhanga, Nan Cheng +3
Modern learning systems work with data that vary widely across domains, but they all ultimately depend on how much structure is already present in the measurements before any model…