Search Results for author:
Found 12 papers, 3 papers with code
ParZC: Parametric Zero-Cost Proxies for Efficient NAS
Recent advancements in Zero-shot Neural Architecture Search (NAS) highlight the efficacy of zero-cost proxies in various NAS benchmarks.
Auto-Prox: Training-Free Vision Transformer Architecture Search via Automatic Proxy Discovery
Based on the discovered zero-cost proxy, we conduct a ViT architecture search in a training-free manner.
TVT: Training-Free Vision Transformer Search on Tiny Datasets
In this paper, for the first time, we investigate how to search in a training-free manner with the help of teacher models and devise an effective Training-free ViT (TVT) search framework.
EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization
In particular, we devise an elaborate search space involving the existing proxies and perform an evolution search to discover the best correlated MQ proxy.
DisWOT: Student Architecture Search for Distillation WithOut Training
In this way, our student architecture search for Distillation WithOut Training (DisWOT) significantly improves the performance of the model in the distillation stage with at least 180$\times$ training acceleration.
Progressive Meta-Pooling Learning for Lightweight Image Classification Model
Practical networks for edge devices adopt shallow depth and small convolutional kernels to save memory and computational cost, which leads to a restricted receptive field.
RD-NAS: Enhancing One-shot Supernet Ranking Ability via Ranking Distillation from Zero-cost Proxies
In this paper, we propose Ranking Distillation one-shot NAS (RD-NAS) to enhance ranking consistency, which utilizes zero-cost proxies as the cheap teacher and adopts the margin ranking loss to distill the ranking knowledge.
Automated Knowledge Distillation via Monte Carlo Tree Search
In this paper, we present Auto-KD, the first automated search framework for optimal knowledge distillation design.
OVO: One-shot Vision Transformer Search with Online distillation
OVO samples sub-nets for both teacher and student networks for better distillation results.
DMFormer: Closing the Gap Between CNN and Vision Transformers
Vision transformers have shown excellent performance in computer vision tasks.
Prior-Guided One-shot Neural Architecture Search
In this paper, we present Prior-Guided One-shot NAS (PGONAS) to strengthen the ranking correlation of supernets.
Multi-trial Neural Architecture Search with Lottery Tickets
Neural architecture search (NAS) has brought significant progress in recent image recognition tasks.
