A new encoding and iterative training-set expansion method for latency prediction in hardware-aware neural architecture search, reporting accuracy gains on GPU, CPU, and embedded targets.
A survey of accelerator architectures for deep neural networks,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
ESM: A Framework for Building Effective Surrogate Models for Hardware-Aware Neural Architecture Search
A new encoding and iterative training-set expansion method for latency prediction in hardware-aware neural architecture search, reporting accuracy gains on GPU, CPU, and embedded targets.