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Daning Cheng

2 accepted papers

2026

FP=XINT: Representing Neural Networks via Low-Bit Series Basis Functions

AAAI 2026technical

Deep neural networks are often over-parameterized, resulting in prohibitive storage and computational costs. A fundamental question is whether a complex network can be re-expressed in terms of a compact set of basis functions without sacrificing accuracy. Motivated by this perspective, we aim to app

Cited by 0SourcePDFScholar
2026

Rethinking Parameter Sharing as Graph Coloring for Structured Compression

ICML 2026poster

Parameter sharing is a key model compression technique, yet existing methods overlook the geometric properties of the loss landscape, often causing severe accuracy degradation under high compression ratios. Inspired by second-order optimization, we propose Curvature-aware Graph Coloring (CGC), a cro…

Cited by 0SourceScholar