6 citations · 19 across the 27 of their papers we have counts for
6 papers · 1 filter
Revisiting Long-Tailed Learning: Insights from an Architectural Perspective
Yuhan Pan, Yanan Sun, Wei Gong
Long-Tailed (LT) recognition has been widely studied to tackle the challenge of imbalanced data distributions in real-world applications. However, the design of neural architecture…
CAP: A Context-Aware Neural Predictor for NAS
Han Ji, Yuqi Feng, Yanan Sun
Neural predictors are effective in boosting the time-consuming performance evaluation stage in neural architecture search (NAS), owing to their direct estimation of unseen architec…
Towards Accurate and Robust Architectures via Neural Architecture Search
Yuwei Ou, Yuqi Feng, Yanan Sun
To defend deep neural networks from adversarial attacks, adversarial training has been drawing increasing attention for its effectiveness. However, the accuracy and robustness resu…
Revisiting Neural Networks for Continual Learning: An Architectural Perspective
Aojun Lu, Tao Feng, Hangjie Yuan +2
Efforts to overcome catastrophic forgetting have primarily centered around developing more effective Continual Learning (CL) methods. In contrast, less attention was devoted to ana…
Genetic Auto-prompt Learning for Pre-trained Code Intelligence Language Models
Chengzhe Feng, Yanan Sun, Ke Li +3
As Pre-trained Language Models (PLMs), a popular approach for code intelligence, continue to grow in size, the computational cost of their usage has become prohibitively expensive.…
A First Step Towards Runtime Analysis of Evolutionary Neural Architecture Search
Zeqiong Lv, Chao Qian, Yanan Sun
Evolutionary neural architecture search (ENAS) employs evolutionary algorithms to find high-performing neural architectures automatically, and has achieved great success. However,…