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代表论文
2022年代表性论文
时间:2022-12-25 作者:

[1]Junbiao Cui, Jiye Liang. Fuzzy learning machine. Proceedings of Advances in Neural Information Processing Systems (NeurIPS), 2022: 36693-36705.

[2]Jiye Liang, Xiaolin Liu, Liang Bai, Fuyuan Cao, Dianhui Wang. Incomplete multi-view clustering via local and global co-regularization. SCIENCE CHINA Information Sciences, 2022, 65(5): 152105.

[3]Qin Yue, Jiye Liang, Junbiao Cui, Liang Bai, Dual bidirectional graph convolutional networks for zero-shot node classification, 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022

[4]Liang Bai, Jiye Liang, Yuxiao Zhao. Self-constrained spectral clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 45(4): 5126-5138.

[5]Liang Bai, Yunxiao Zhao, Jiye Liang. Self-supervised spectral clustering with exemplar constraints, Pattern Recognition, 2022, 132: 108975.

[6]Liang Bai, Jiye Liang. A categorical data clustering framework on graph representation. Pattern Recognition, 2022, 128:108694.

[7]Qingqiang Chen, Fuyuan Cao, Ying Xing, Jiye Liang. Instance selection: A bayesian decision theory perspective, AAAI Conference on Artificial Intelligence (AAAI), 2022 :6287-6294

[8]Yunxia Wang, Fuyuan Cao, Kui Yu, Jiye Liang. Efficient causal structure learning from multiple interventional datasets with unknown targets, AAAI Conference on Artificial Intelligence (AAAI), 2022: 8584-8593.

[9]Wei Wei, Yujia Zhang, Jiye Liang, Lin Li, Yuze Li. Controlling underestimation bias in reinforcement learning via quasi-median operation.Proceedings of the AAAI Conference on Artificial Intelligence, 2022, 36(8): 8621-8628.

[10]Jie Wang, Jianqing Liang, Jiye Liang, Kaixuan Yao. GUIDE: Training deep graph neural networks via guided dropout over edges. IEEE Transactions on Neural Networks and Learning Systems. DOI: 10.1109/TNNLS.2022.317287.

[11]XinyaoGuo, Wei Wei, Jianqing Liang, Chuangyin Dang, Jiye Liang. Metric learning via perturbing hard-to-classify instances. Pattern Recognition, 2022, 132: 108928.

[12]Anhui Tan, Jiye Liang, Wei-zhi Wu, Jia Zhang. Semi-supervised partial multi-label classification via consistency learning, Pattern Recognition,2022, 131:108839.

[13]Jing Liu, Fuyuan Cao, Jiye Liang. Centroids-guided deep multi-view K-means clustering, Information Sciences, 2022: 876-896.

[14]ZhihaoGuo, Feng Wang, Kaixuan Yao, Jiye Liang, Zhiqiang Wang. Multi-scale variational graph autoencoder for link prediction. In Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining(WSDM '22), online,2022, 334–342.

[15]Erliang Yao, Deyu Li, YanhuiZhai, Chao Zhang. Multilabel feature selection based on relative discernibility pair matrix. IEEE Transactions on Fuzzy Systems, 2022, 30, 7, 2388-2401.

[16]HexiangBai, Deyu Li, Yong Ge, Jinfeng Wang, Feng Cao. Spatial rough set-based geographical detectors for nominal target variables. Information Sciences, 2022, 586:525-539.

[17]Xin Wen, Deyu Li, Chao Zhang, YanhuiZhai. A weighted ML-KNN based on discernibility of attributes to heterogeneous sample pairs. Information Processing & Management, 2022, 59, 103053.

[18]HushengGuo, Hai Li, QiaoyanRen, Wenjian Wang. Concept drift type identification based on multi-sliding windows. Information Sciences, 2022, 586: 1-23.

[19]杜航原, 王文剑, 白亮. 一种融合伴随信息的网络表示学习模型. 软件学报, 2022, DOI:10.13328/j.cnki.jos.006486.

[20]王克琪, 钱宇华, 梁吉业, 刘畅, 黄琴, 陈路, 贾洁茹. 局部–全局关系耦合的低照度图像增强, 中国科学:信息科学. 2022, 52(3):443-460.

[21]姜高霞, 王文剑. 面向回归任务的数值型标签噪声过滤算法. 计算机研究与发展, 2022, 59(8): 1639-1652.

[22]张虎, 王宇杰, 谭红叶, 李茹. 基于MHSA和句法关系增强的机器阅读理解方法研究, 自动化学报, 2022, 48(11): 2718-2728.

[23]刘晓琳, 白亮, 赵兴旺, 梁吉业. 基于多阶近邻融合的不完整多视图聚类算法. 软件学报, 2022, 33(4): 1354-1372.

[24]郭虎升, 任巧燕, 王文剑. 基于时序窗口的概念漂移类型检测. 计算机研究与发展, 2022, 59(1):127-143.