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MobileNetV3
The dataset used in the paper for Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning -
HW-NAS-Bench-201
The dataset used in the paper for Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning -
HW-NAS-Bench
The dataset used in the paper for Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning -
ProxylessNAS: Direct neural architecture search on target task and hardware
The authors propose a proxyless NAS algorithm that can be used for efficient deployment. -
Monas: Multi-objective neural architecture search using reinforcement learning
The authors propose a multi-objective neural architecture search using reinforcement learning. -
Multi-objective Differentiable Neural Architecture Search
The authors propose a novel hardware-aware differentiable NAS algorithm for profiling the Pareto front in multi-objective problems. -
NAS-Bench-201
The dataset used in the paper is the NAS-Bench-201 dataset, which is a benchmark for neural architecture search. -
Joint-DetNAS: Upgrade Your Detector with NAS, Pruning and Dynamic Distillation
Joint-DetNAS is a unified framework for object detection that jointly optimizes NAS, pruning, and dynamic distillation.
