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most citedZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradients

19 citations · 22 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CV2023★ 1 cited

Efficient Low-rank Backpropagation for Vision Transformer Adaptation

Yuedong Yang, Hung-Yueh Chiang, Guihong Li +2

The increasing scale of vision transformers (ViT) has made the efficient fine-tuning of these large models for specific needs a significant challenge in various applications. This…

cs.LG2023★ 1 cited

Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities

Guihong Li, Duc Hoang, Kartikeya Bhardwaj +3

Recently, zero-shot (or training-free) Neural Architecture Search (NAS) approaches have been proposed to liberate NAS from the expensive training process. The key idea behind zero-…

cs.LG2023

TIPS: Topologically Important Path Sampling for Anytime Neural Networks

Guihong Li, Kartikeya Bhardwaj, Yuedong Yang +1

Anytime neural networks (AnytimeNNs) are a promising solution to adaptively adjust the model complexity at runtime under various hardware resource constraints. However, the manuall…

cs.LG2023★ 19 cited

ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradients

Guihong Li, Yuedong Yang, Kartikeya Bhardwaj +1

Neural Architecture Search (NAS) is widely used to automatically obtain the neural network with the best performance among a large number of candidate architectures. To reduce the…

cs.CV2023

Efficient On-device Training via Gradient Filtering

Yuedong Yang, Guihong Li, Radu Marculescu

Despite its importance for federated learning, continuous learning and many other applications, on-device training remains an open problem for EdgeAI. The problem stems from the la…