Qizhou Wang

According to our database, Qizhou Wang authored at least 29 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Scheduling optimization of underground mine trackless transportation based on improved estimation of distribution algorithm.

Ning Li, Yahui Wu, Haiwang Ye, Liguan Wang, Qizhou Wang, Mingtao Jia

Expert Syst. Appl., 2024

Combination prediction of underground mine rock drilling time based on seasonal and trend decomposition using Loess.

Ning Li, Ding Liu, Liguan Wang, Haiwang Ye, Qizhou Wang, Dairong Yan, Shugang Zhao

Eng. Appl. Artif. Intell., 2024

Unlearning with Control: Assessing Real-world Utility for Large Language Model Unlearning.

Qizhou Wang, Bo Han, Puning Yang, Jianing Zhu, Tongliang Liu, Masashi Sugiyama

CoRR, 2024

Do CLIPs Always Generalize Better than ImageNet Models?

Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang

CoRR, 2024

2023

Underground mine truck travel time prediction based on stacking integrated learning.

Ning Li, Yahui Wu, Qizhou Wang, Haiwang Ye, Liguan Wang, Mingtao Jia, Shugang Zhao

Eng. Appl. Artif. Intell., April, 2023

Are All Unseen Data Out-of-Distribution?

Songming Zhang, Yuxiao Luo, Qizhou Wang, Haoang Chi, Weikai Li, Bo Han, Jinyan Li

CoRR, 2023

Artificial intelligence optical hardware empowers high-resolution hyperspectral video understanding at 1.2 Tb/s.

Maksim Makarenko, Qizhou Wang, Arturo Burguete-Lopez, Silvio Giancola, Bernard Ghanem, Luca Passone, Andrea Fratalocchi

CoRR, 2023

Open-Set Graph Anomaly Detection via Normal Structure Regularisation.

Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray L. Buntine, Christopher Leckie

CoRR, 2023

Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources.

Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning to Augment Distributions for Out-of-distribution Detection.

Qizhou Wang, Zhen Fang, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Out-of-distribution Detection with Implicit Outlier Transformation.

Qizhou Wang, Junjie Ye, Feng Liu, Quanyu Dai, Marcus Kalander, Tongliang Liu, Jianye Hao, Bo Han

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Cross-Domain Graph Anomaly Detection via Anomaly-Aware Contrastive Alignment.

Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray L. Buntine, Christopher Leckie

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Instance-Dependent Positive and Unlabeled Learning With Labeling Bias Estimation.

Chen Gong, Qizhou Wang, Tongliang Liu, Bo Han, Jane You, Jian Yang, Dacheng Tao

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Towards Lightweight Black-Box Attacks against Deep Neural Networks.

Chenghao Sun, Yonggang Zhang, Chaoqun Wan, Qizhou Wang, Ya Li, Tongliang Liu, Bo Han, Xinmei Tian

CoRR, 2022

Improved estimation of canopy water status in maize using UAV-based digital and hyperspectral images.

Meiyan Shu, Qizhou Wang, Shuaipeng Fei, Xiaohong Yang, Zhu Jinyu, Meng Lei, Baoguo Li, Yuntao Ma

Comput. Electron. Agric., 2022

ENDASh: Embedding Neighbourhood Dissimilarity with Attribute Shuffling for Graph Anomaly Detection.

Qizhou Wang, Mahsa Salehi, Jia Shun Low, Wray L. Buntine, Christopher Leckie

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Watermarking for Out-of-distribution Detection.

Qizhou Wang, Feng Liu, Yonggang Zhang, Jing Zhang, Chen Gong, Tongliang Liu, Bo Han

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Towards Lightweight Black-Box Attack Against Deep Neural Networks.

Chenghao Sun, Yonggang Zhang, Chaoqun Wan, Qizhou Wang, Ya Li, Tongliang Liu, Bo Han, Xinmei Tian

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Real-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders.

Maksim Makarenko, Arturo Burguete-Lopez, Qizhou Wang, Fedor Getman, Silvio Giancola, Bernard Ghanem, Andrea Fratalocchi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

SDA-GAN: Unsupervised Image Translation Using Spectral Domain Attention-Guided Generative Adversarial Network.

Qizhou Wang, Maksim Makarenko

CoRR, 2021

Robust and Scalable Flat-Optics on Flexible Substrates via Evolutionary Neural Networks.

Maksim Makarenko, Qizhou Wang, Arturo Burguete-Lopez, Fedor Getman, Andrea Fratalocchi

Adv. Intell. Syst., 2021

A Dimensionality-Driven Approach for Unsupervised Out-of-distribution Detection.

Qizhou Wang, Sarah M. Erfani, Christopher Leckie, Michael E. Houle

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Probabilistic Margins for Instance Reweighting in Adversarial Training.

Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fraud Detection under Multi-Sourced Extremely Noisy Annotations.

Chuang Zhang, Qizhou Wang, Tengfei Liu, Xun Lu, Jin Hong, Bo Han, Chen Gong

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Learning with Group Noise.

Qizhou Wang, Jiangchao Yao, Chen Gong, Tongliang Liu, Mingming Gong, Hongxia Yang, Bo Han

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model.

Qizhou Wang, Bo Han, Tongliang Liu, Gang Niu, Jian Yang, Chen Gong

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

A game method for improving the interpretability of convolution neural network.

Jinwei Zhao, Qizhou Wang, Fuqiang Zhang, Wanli Qiu, Yufei Wang, Yu Liu, Guo Xie, Weigang Ma, Bin Wang, Xinhong Hei

CoRR, 2019

2018

How to improve the interpretability of kernel learning.

Jinwei Zhao, Qizhou Wang, Yufei Wang, Xinhong Hei, Yu Liu, Zhenghao Shi

CoRR, 2018

How far from automatically interpreting deep learning.

Jinwei Zhao, Qizhou Wang, Yufei Wang, Xinhong Hei, Yu Liu

CoRR, 2018