A post-training method that nests a lower-bit weight model inside a full-bit quantized model so devices can switch precision on the fly from one stored model.
Secaas-based partially observable defense model for iiot against advanced persistent threats,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
NestQuant: Post-Training Integer-Nesting Quantization for On-Device DNN
A post-training method that nests a lower-bit weight model inside a full-bit quantized model so devices can switch precision on the fly from one stored model.