Deep Learning

NASViT: Neural Architecture Search for Efficient Vision Transformer with Gradient Conflict-Aware Supernet Training

Propose gradient conflict-aware training to improve supernet-based NAS and develop a family of optimized hybrid CNN/ViT networks that achieve state-of-the-art performance Pareto.

AlphaNet: Improved Training of Supernet with Alpha-Divergence

Develop AlphaNet to improve the supernet-based NAS with a more generalized alpha-divergence-based knowledge distillation and achieve state-of-the-art performance Pareto.

AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling

Develop AttentiveNAS that focuses on improving the sampling strategy for supernet-based NAS to achieve state-of-the-art performance Pareto.

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