33 citations · 67 across the 23 of their papers we have counts for
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cs.LG2023
Rethinking SIGN Training: Provable Nonconvex Acceleration without First- and Second-Order Gradient Lipschitz
Tao Sun, Congliang Chen, Peng Qiao +3
Sign-based stochastic methods have gained attention due to their ability to achieve robust performance despite using only the sign information for parameter updates. However, the c…
cs.CV2023★ 3 cited
PVP: Pre-trained Visual Parameter-Efficient Tuning
Zhao Song, Ke Yang, Naiyang Guan +3
Large-scale pre-trained transformers have demonstrated remarkable success in various computer vision tasks. However, it is still highly challenging to fully fine-tune these models…
cs.CV2023
Towards Vision Transformer Unrolling Fixed-Point Algorithm: a Case Study on Image Restoration
Peng Qiao, Sidun Liu, Tao Sun +2
The great success of Deep Neural Networks (DNNs) has inspired the algorithmic development of DNN-based Fixed-Point (DNN-FP) for computer vision tasks. DNN-FP methods, trained by Ba…