NAS22
* *Neural Architecture Search: Lightweight NAS Challenge (NAS)
* DNAS:A Decoupled Global Neural Architecture Search Method
* Hot-started NAS for Task-specific Embedded Applications
* Less is More: Proxy Datasets in NAS approaches
* Network Amplification with Efficient MACs Allocation
* Searching for Energy-Efficient Hybrid Adder-Convolution Neural Networks
* SpiderNet: Hybrid Differentiable-Evolutionary Architecture Search via Train-Free Metrics
7 for NAS22
NAS23
* *Neural Architecture Search: Lightweight NAS Challenge (NAS)
* A2-Aug: Adaptive Automated Data Augmentation
* AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection
* Exploring the Potential of Neural Dataset Search
* Fast GraspNeXt: A Fast Self-Attention Neural Network Architecture for Multi-task Learning in Computer Vision Tasks for Robotic Grasping on the Edge
* Hardware-aware NAS by Genetic Optimisation with a Design Space Exploration Simulator
* Pareto-aware Neural Architecture Generation for Diverse Computational Budgets
* PerfHD: Efficient ViT Architecture Performance Ranking using Hyperdimensional Computing
* Systematic Architectural Design of Scale Transformed Attention Condenser DNNs via Multi-Scale Class Representational Response Similarity Analysis
9 for NAS23
NAS24
* *Neural Architecture Search: Lightweight NAS Challenge (NAS)
* CSCO: Connectivity Search of Convolutional Operators
* CycleGANAS: Differentiable Neural Architecture Search for CycleGAN
* devil is in discretization discrepancy. Robustifying Differentiable NAS with Single-Stage Searching Protocol, The
* GRASP-GCN: Graph-Shape Prioritization for Neural Architecture Search under Distribution Shifts
* QuantNAS: Quantization-aware Neural Architecture Search For Efficient Deployment On Mobile Device
* UP-NAS: Unified Proxy for Neural Architecture Search
7 for NAS24