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Yunquan Zhang

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

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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…

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