41 citations · 189 across the 18 of their papers we have counts for
5 papers · 1 filter
Stretchable Cells Help DARTS Search Better
Tao Huang, Shan You, Yibo Yang +4
Differentiable neural architecture search (DARTS) has gained much success in discovering flexible and diverse cell types. To reduce the evaluation gap, the supernet is expected to…
Data Agnostic Filter Gating for Efficient Deep Networks
Xiu Su, Shan You, Tao Huang +5
To deploy a well-trained CNN model on low-end computation edge devices, it is usually supposed to compress or prune the model under certain computation budget (e.g., FLOPs). Curren…
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding
Yibo Yang, Hongyang Li, Shan You +3
Neural architecture search (NAS) aims to produce the optimal sparse solution from a high-dimensional space spanned by all candidate connections. Current gradient-based NAS methods…
Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking Fairness and Algorithm Utility
Sen Cui, Weishen Pan, Changshui Zhang +1
Bipartite ranking, which aims to learn a scoring function that ranks positive individuals higher than negative ones from labeled data, is widely adopted in various applications whe…
GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet
Shan You, Tao Huang, Mingmin Yang +3
Training a supernet matters for one-shot neural architecture search (NAS) methods since it serves as a basic performance estimator for different architectures (paths). Current meth…