no code implementations • 2 Feb 2025 • Mengping Yang, Zhe Wang, Ziqiu Chi, Dongdong Li, Wenli Du
To improve the synthesis performance of GANs in low-data regimes, existing approaches use various data augmentation techniques to enlarge the training sets.
no code implementations • 27 Oct 2024 • Longyan Li, Chao Ning, Guangsheng Pan, Leiqi Zhang, Wei Gu, Liang Zhao, Wenli Du, Mohammad Shahidehpour
Based upon this model, a data-driven RAJIT scheme is developed for the real-time rolling optimization of AHMGs.
no code implementations • 18 Jul 2024 • Peng Liao, Xilu Wang, Yaochu Jin, Wenli Du
Arguably, due to the small model trap problem in multi-objective neural architecture search (MO-NAS) based on a supernet, existing approaches may fail to maintain large models.
1 code implementation • 24 Jun 2024 • Xutao Ma, Chao Ning, Wenli Du
As an application of the proposed differentiable DRO layers, we develop a novel decision-focused learning pipeline for contextual distributionally robust decision-making tasks and compare it with the prediction-focused approach in experiments.
no code implementations • 9 Jan 2024 • Wanting Zhang, Wei Du, Guo Yu, Renchu He, Wenli Du, Yaochu Jin
On the basis of the proposed model, a dual-stage evolutionary algorithm driven by heuristic rules (denoted by DSEA/HR) is developed, where the dual-stage search mechanism consists of global search and local refinement.
1 code implementation • CVPR 2023 • Peng Liao, Yaochu Jin, Wenli Du
In deep learning, this is usually achieved by sharing a common neural network architecture and jointly training the weights.
no code implementations • 22 Jul 2022 • Guo Yu, Lianbo Ma, Wei Du, Wenli Du, Yaochu Jin
Recent years have seen the rapid development of fairness-aware machine learning in mitigating unfairness or discrimination in decision-making in a wide range of applications.
1 code implementation • 22 Jun 2021 • Jinjin Xu, Yaochu Jin, Wenli Du
Data-driven optimization has found many successful applications in the real world and received increased attention in the field of evolutionary optimization.
1 code implementation • 16 Feb 2021 • Jinjin Xu, Yaochu Jin, Wenli Du, Sai Gu
Data-driven evolutionary optimization has witnessed great success in solving complex real-world optimization problems.
1 code implementation • 7 Mar 2020 • Jinjin Xu, Wenli Du, Ran Cheng, Wangli He, Yaochu Jin
Learning over massive data stored in different locations is essential in many real-world applications.
no code implementations • 8 Jan 2020 • Yang Tang, Chaoqiang Zhao, Jianrui Wang, Chongzhen Zhang, Qiyu Sun, Weixing Zheng, Wenli Du, Feng Qian, Juergen Kurths
Second, we review the visual-based environmental perception and understanding methods based on deep learning, including deep learning-based monocular depth estimation, monocular ego-motion prediction, image enhancement, object detection, semantic segmentation, and their combinations with traditional vSLAM frameworks.