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ORCIDLing Chen 0006
Person information
- affiliation: University of Technology Sydney, Centre for Artificial Intelligence, Broadway, NSW, Australia
- affiliation (former): University of Hannover, L3S Research Center, Germany
- affiliation (PhD 2008): Nanyang Technological University, Singapore
Other persons with the same name
- Ling Chen — disambiguation page
- Ling Chen 0001
![[0000-0003-1934-5992]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0003-1934-5992")
— Zhejiang University, College of Computer Science and Technology, China - Ling Chen 0003 — Central South University, School of Information Science and Engineering, Changsha, China
- Ling Chen 0004 — University of Queensland, School of Information Technology and Electrical Engineering, Brisbane, QLD, Australia
- Ling Chen 0005 — Yangzhou University, School of Information Engineering, China
- Ling Chen 0007 — Borough of Manhattan Community College CUNY, New York, NY, USA
- Ling Chen 0008 — Dalian University of Technology, MOE Key Laboratory for Precision and Non-Traditional Machining Technology, China
- Ling Chen 0009 — Beijing Forestry University, State Forestry Administration Key Laboratory of Forest Resources and Environmental Management, China (and 1 more)
- Ling Chen 0010 — Southwest University, College of Electronic Information Engineering, Chongqing, China (and 1 more)
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Books and Theses
- 2007
[b1]Ling Chen:
Discovering association rules from structural evolution of tree structured web data. Nanyang Technological University, Singapore, 2007
Journal Articles
- 2023
- [j34]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Gangyan Xu, Chengqi Zhang:
Shared dynamics learning for large-scale traveling salesman problem. Adv. Eng. Informatics 56: 102005 (2023) - [j33]Xuhui Fan, Yaqiong Li, Ling Chen, Bin Li, Scott A. Sisson:
Hawkes Processes With Stochastic Exogenous Effects for Continuous-Time Interaction Modelling. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1848-1861 (2023) - [j32]Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang:
Bidirectional Spatial-Temporal Adaptive Transformer for Urban Traffic Flow Forecasting. IEEE Trans. Neural Networks Learn. Syst. 34(10): 6913-6925 (2023) - 2022
- [j31]Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Scott A. Sisson:
Smoothing graphons for modelling exchangeable relational data. Mach. Learn. 111(1): 319-344 (2022) - [j30]Hong Yang, Ling Chen, Shirui Pan, Haishuai Wang, Peng Zhang:
Discrete embedding for attributed graphs. Pattern Recognit. 123: 108368 (2022) - [j29]Yunqiu Xu, Meng Fang, Ling Chen, Gangyan Xu, Yali Du, Chengqi Zhang:
Reinforcement Learning With Multiple Relational Attention for Solving Vehicle Routing Problems. IEEE Trans. Cybern. 52(10): 11107-11120 (2022) - [j28]Wei Wu, Bin Li, Ling Chen, Junbin Gao, Chengqi Zhang:
A Review for Weighted MinHash Algorithms. IEEE Trans. Knowl. Data Eng. 34(6): 2553-2573 (2022) - 2021
- [j27]Bo Han, Ivor W. Tsang, Xiaokui Xiao, Ling Chen, Sai-Fu Fung, Celina Ping Yu:
Privacy-Preserving Stochastic Gradual Learning. IEEE Trans. Knowl. Data Eng. 33(8): 3129-3140 (2021) - 2020
- [j26]Wenhe Liu, Xiaojun Chang, Ling Chen, Dinh Phung, Xiaoqin Zhang, Yi Yang, Alexander G. Hauptmann:
Pair-based Uncertainty and Diversity Promoting Early Active Learning for Person Re-identification. ACM Trans. Intell. Syst. Technol. 11(2): 21:1-21:15 (2020) - [j25]Xingzhong Du, Hongzhi Yin, Ling Chen, Yang Wang, Yi Yang, Xiaofang Zhou:
Personalized Video Recommendation Using Rich Contents from Videos. IEEE Trans. Knowl. Data Eng. 32(3): 492-505 (2020) - [j24]Xiaowei Zhao, Jun Guo, Feiping Nie, Ling Chen, Zhihui Li, Huaxiang Zhang:
Joint Principal Component and Discriminant Analysis for Dimensionality Reduction. IEEE Trans. Neural Networks Learn. Syst. 31(2): 433-444 (2020) - 2019
- [j23]Bozhong Liu, Ling Chen, Xingquan Zhu, Weidong Qiu:
Encrypted data indexing for the secure outsourcing of spectral clustering. Knowl. Inf. Syst. 60(3): 1307-1328 (2019) - [j22]Kun Zhan, Xiaojun Chang, Junpeng Guan, Ling Chen, Zhigang Ma, Yi Yang:
Adaptive Structure Discovery for Multimedia Analysis Using Multiple Features. IEEE Trans. Cybern. 49(5): 1826-1834 (2019) - [j21]Minnan Luo, Caixia Yan, Qinghua Zheng, Xiaojun Chang, Ling Chen, Feiping Nie:
Discrete Multi-Graph Clustering. IEEE Trans. Image Process. 28(9): 4701-4712 (2019) - [j20]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang, Philip S. Yu:
Improved Consistent Weighted Sampling Revisited. IEEE Trans. Knowl. Data Eng. 31(12): 2332-2345 (2019) - [j19]Bo Han, Ivor W. Tsang, Ling Chen, Joey Tianyi Zhou, Celina Ping Yu:
Beyond Majority Voting: A Coarse-to-Fine Label Filtration for Heavily Noisy Labels. IEEE Trans. Neural Networks Learn. Syst. 30(12): 3774-3787 (2019) - [j18]Yaqing Wang, Chunyan Feng, Ling Chen, Hongzhi Yin, Caili Guo, Yunfei Chu:
User identity linkage across social networks via linked heterogeneous network embedding. World Wide Web 22(6): 2611-2632 (2019) - 2018
- [j17]Lianhua Chi, Bin Li, Xingquan Zhu, Shirui Pan, Ling Chen:
Hashing for Adaptive Real-Time Graph Stream Classification With Concept Drifts. IEEE Trans. Cybern. 48(5): 1591-1604 (2018) - [j16]Wei Wu, Bin Li, Ling Chen, Xingquan Zhu, Chengqi Zhang:
K-Ary Tree Hashing for Fast Graph Classification. IEEE Trans. Knowl. Data Eng. 30(5): 936-949 (2018) - [j15]Bo Han, Ivor W. Tsang, Ling Chen, Celina Ping Yu, Sai-Fu Fung:
Progressive Stochastic Learning for Noisy Labels. IEEE Trans. Neural Networks Learn. Syst. 29(10): 5136-5148 (2018) - 2017
- [j14]Haishuai Wang, Jia Wu, Shirui Pan, Peng Zhang, Ling Chen:
Towards large-scale social networks with online diffusion provenance detection. Comput. Networks 114: 154-166 (2017) - [j13]Weiqing Wang, Hongzhi Yin, Ling Chen, Yizhou Sun, Shazia Wasim Sadiq, Xiaofang Zhou:
ST-SAGE: A Spatial-Temporal Sparse Additive Generative Model for Spatial Item Recommendation. ACM Trans. Intell. Syst. Technol. 8(3): 48:1-48:25 (2017) - [j12]Haishuai Wang, Peng Zhang, Xingquan Zhu, Ivor Wai-Hung Tsang, Ling Chen, Chengqi Zhang, Xindong Wu:
Incremental Subgraph Feature Selection for Graph Classification. IEEE Trans. Knowl. Data Eng. 29(1): 128-142 (2017) - [j11]Hongzhi Yin, Weiqing Wang, Hao Wang, Ling Chen, Xiaofang Zhou:
Spatial-Aware Hierarchical Collaborative Deep Learning for POI Recommendation. IEEE Trans. Knowl. Data Eng. 29(11): 2537-2551 (2017) - 2016
- [j10]Yongshan Zhang, Jia Wu, Zhihua Cai, Peng Zhang, Ling Chen:
Memetic Extreme Learning Machine. Pattern Recognit. 58: 135-148 (2016) - 2015
- [j9]Hongzhi Yin, Bin Cui, Ling Chen, Zhiting Hu, Chengqi Zhang:
Modeling Location-Based User Rating Profiles for Personalized Recommendation. ACM Trans. Knowl. Discov. Data 9(3): 19:1-19:41 (2015) - [j8]Hongzhi Yin, Bin Cui, Ling Chen, Zhiting Hu, Xiaofang Zhou:
Dynamic User Modeling in Social Media Systems. ACM Trans. Inf. Syst. 33(3): 10:1-10:44 (2015) - 2014
- [j7]Hongzhi Yin, Bin Cui, Yizhou Sun, Zhiting Hu, Ling Chen:
LCARS: A Spatial Item Recommender System. ACM Trans. Inf. Syst. 32(3): 11:1-11:37 (2014) - 2013
- [j6]Jie Tang, Ling Chen, Irwin King, Jianyong Wang:
Introduction to Special section on Large-scale Data Mining. Data Knowl. Eng. 87: 355-356 (2013) - [j5]Bin Li, Ling Chen, Xingquan Zhu, Chengqi Zhang:
Noisy but non-malicious user detection in social recommender systems. World Wide Web 16(5-6): 677-699 (2013) - 2009
- [j4]Ling Chen, Sourav S. Bhowmick, Wolfgang Nejdl:
COWES: Web user clustering based on evolutionary web sessions. Data Knowl. Eng. 68(10): 867-885 (2009) - [j3]Ling Chen, Sourav S. Bhowmick, Wolfgang Nejdl:
NEAR-Miner: Mining Evolution Associations of Web Site Directories for Efficient Maintenance of Web Archives. Proc. VLDB Endow. 2(1): 1150-1161 (2009) - 2006
- [j2]Ling Chen, Sourav S. Bhowmick, Liang-Tien Chia:
FRACTURE mining: Mining frequently and concurrently mutating structures from historical XML documents. Data Knowl. Eng. 59(2): 320-347 (2006) - [j1]Qiankun Zhao, Ling Chen, Sourav S. Bhowmick, Sanjay Madria:
XML structural delta mining: Issues and challenges. Data Knowl. Eng. 59(3): 627-651 (2006)
Conference and Workshop Papers
- 2023
- [c69]Jiaxu Zhao, Meng Fang, Zijing Shi, Yitong Li, Ling Chen, Mykola Pechenizkiy:
CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models. ACL (1) 2023: 13538-13556 - [c68]Hexuan Weng, Yanbin Liu, Ling Chen:
Spatial Bottleneck Transformer for Cellular Traffic Prediction in the Urban City. AI (1) 2023: 265-276 - [c67]Jiaxi Li, Guansong Pang, Ling Chen, Mohammad-Reza Namazi-Rad:
HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural Networks. DSAA 2023: 1-10 - [c66]Zijing Shi, Yunqiu Xu, Meng Fang, Ling Chen:
Self-imitation Learning for Action Generation in Text-based Games. EACL 2023: 703-726 - [c65]Zihan Zhang, Meng Fang, Fanghua Ye, Ling Chen, Mohammad-Reza Namazi-Rad:
Turn-Level Active Learning for Dialogue State Tracking. EMNLP 2023: 7705-7719 - [c64]Zihan Zhang, Meng Fang, Ling Chen, Mohammad-Reza Namazi-Rad, Jun Wang:
How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances. EMNLP 2023: 8289-8311 - [c63]Zihan Zhang, Meng Fang, Ling Chen, Mohammad-Reza Namazi-Rad:
CITB: A Benchmark for Continual Instruction Tuning. EMNLP (Findings) 2023: 9443-9455 - [c62]Wei Wu, Bin Li, Ling Chen, Junbin Gao, Chengqi Zhang:
A Review for Weighted MinHash Algorithms (Extended abstract). ICDE 2023: 3785-3786 - [c61]Zijing Shi, Meng Fang, Yunqiu Xu, Ling Chen, Yali Du:
Stay Moral and Explore: Learn to Behave Morally in Text-based Games. ICLR 2023 - 2022
- [c60]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, Chengqi Zhang:
Perceiving the World: Question-guided Reinforcement Learning for Text-based Games. ACL (1) 2022: 538-560 - [c59]Shaoshen Wang, Yanbin Liu, Ling Chen, Chengqi Zhang:
Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection. IJCNN 2022: 1-8 - [c58]Zihan Zhang, Meng Fang, Ling Chen, Mohammad-Reza Namazi-Rad:
Is Neural Topic Modelling Better than Clustering? An Empirical Study on Clustering with Contextual Embeddings for Topics. NAACL-HLT 2022: 3886-3893 - 2021
- [c57]Shaoshen Wang, Ling Chen, Farookh Khadeer Hussain, Chengqi Zhang:
Semi-supervised Variational Multi-view Anomaly Detection. APWeb/WAIM (1) 2021: 125-133 - [c56]Weichao Wang, Wei Gao, Shi Feng, Ling Chen, Daling Wang:
Adaptive Posterior Knowledge Selection for Improving Knowledge-Grounded Dialogue Generation. CIKM 2021: 1989-1998 - [c55]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Chengqi Zhang:
Generalization in Text-based Games via Hierarchical Reinforcement Learning. EMNLP (Findings) 2021: 1343-1353 - [c54]Shaoshen Wang, Yanbin Liu, Ling Chen, Chengqi Zhang:
Cross-aligned and Gumbel-refactored Autoencoders for Multi-view Anomaly Detection. ICTAI 2021: 1368-1375 - [c53]Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Scott A. Sisson:
Decoupling Sparsity and Smoothness in Dirichlet Belief Networks. ECML/PKDD (2) 2021: 148-163 - 2020
- [c52]Yunqiu Xu, Ling Chen, Meng Fang, Yang Wang, Chengqi Zhang:
Deep Reinforcement Learning with Transformers for Text Adventure Games. CoG 2020: 65-72 - [c51]Hong Yang, Ling Chen, Minglong Lei, Lingfeng Niu, Chuan Zhou, Peng Zhang:
Discrete Embedding for Latent Networks. IJCAI 2020: 1223-1229 - [c50]Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Zheng Yu, Scott A. Sisson:
Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling. IJCAI 2020: 2470-2476 - [c49]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, Chengqi Zhang:
Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games. NeurIPS 2020 - 2019
- [c48]Yanbin Liu, Yan Yan, Ling Chen, Yahong Han, Yi Yang:
Adaptive Sparse Confidence-Weighted Learning for Online Feature Selection. AAAI 2019: 4408-4415 - [c47]Ke Sun, Tieyun Qian, Hongzhi Yin, Tong Chen, Yiqi Chen, Ling Chen:
What Can History Tell Us? CIKM 2019: 1593-1602 - [c46]Dong Wen, Lu Qin, Ying Zhang, Lijun Chang, Ling Chen:
Enumerating k-Vertex Connected Components in Large Graphs. ICDE 2019: 52-63 - [c45]Hong Yang, Shirui Pan, Ling Chen, Chuan Zhou, Peng Zhang:
Low-Bit Quantization for Attributed Network Representation Learning. IJCAI 2019: 4047-4053 - [c44]Xuhui Fan, Bin Li, Caoyuan Li, Scott A. Sisson, Ling Chen:
Scalable Deep Generative Relational Model with High-Order Node Dependence. NeurIPS 2019: 12637-12647 - 2018
- [c43]Wenhe Liu, Xiaojun Chang, Ling Chen, Yi Yang:
Semi-Supervised Bayesian Attribute Learning for Person Re-Identification. AAAI 2018: 7162-7169 - [c42]Jiamiao Wang, Ling Chen, Lu Qin, Xindong Wu:
ASTM: An Attentional Segmentation Based Topic Model for Short Texts. ICDM 2018: 577-586 - [c41]Hong Yang, Shirui Pan, Peng Zhang, Ling Chen, Defu Lian, Chengqi Zhang:
Binarized attributed network embedding. ICDM 2018: 1476-1481 - [c40]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang:
Efficient Attributed Network Embedding via Recursive Randomized Hashing. IJCAI 2018: 2861-2867 - [c39]Chunyang Liu, Ling Chen, Ivor W. Tsang, Hongzhi Yin:
Towards the Learning of Weighted Multi-label Associative Classifiers. IJCNN 2018: 1-7 - 2017
- [c38]Bozhong Liu, Ling Chen, Xingquan Zhu, Ying Zhang, Chengqi Zhang, Weidong Qiu:
Protecting Location Privacy in Spatial Crowdsourcing using Encrypted Data. EDBT 2017: 478-481 - [c37]Pingbo Pan, Jiashi Feng, Ling Chen, Yi Yang:
Online compressed robust PCA. IJCNN 2017: 1041-1048 - [c36]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang:
Consistent Weighted Sampling Made More Practical. WWW 2017: 1035-1043 - 2016
- [c35]Bozhong Liu, Ling Chen, Chunyang Liu, Chengqi Zhang, Weidong Qiu:
Mining Co-locations from Continuously Distributed Uncertain Spatial Data. APWeb (1) 2016: 66-78 - [c34]Weiqing Wang, Hongzhi Yin, Shazia Wasim Sadiq, Ling Chen, Min Xie, Xiaofang Zhou:
SPORE: A sequential personalized spatial item recommender system. ICDE 2016: 954-965 - [c33]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang:
Canonical Consistent Weighted Sampling for Real-Value Weighted Min-Hash. ICDM 2016: 1287-1292 - [c32]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang:
Cross-View Feature Hashing for Image Retrieval. PAKDD (1) 2016: 203-214 - [c31]Bo Han, Ivor W. Tsang, Ling Chen:
On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent. ECML/PKDD (1) 2016: 665-680 - [c30]Kaisong Song, Wei Gao, Ling Chen, Shi Feng, Daling Wang, Chengqi Zhang:
Build Emotion Lexicon from the Mood of Crowd via Topic-Assisted Joint Non-negative Matrix Factorization. SIGIR 2016: 773-776 - [c29]Kaisong Song, Ling Chen, Wei Gao, Shi Feng, Daling Wang, Chengqi Zhang:
PerSentiment: A Personalized Sentiment Classification System for Microblog Users. WWW (Companion Volume) 2016: 255-258 - 2015
- [c28]Haishuai Wang, Peng Zhang, Ling Chen, Chengqi Zhang:
SocialAnalysis: A Real-Time Query and Mining System from Social Media Data Streams. ADC 2015: 318-322 - [c27]Haishuai Wang, Peng Zhang, Ivor W. Tsang, Ling Chen, Chengqi Zhang:
Defragging Subgraph Features for Graph Classification. CIKM 2015: 1687-1690 - [c26]Kaisong Song, Shi Feng, Wei Gao, Daling Wang, Ling Chen, Chengqi Zhang:
Build Emotion Lexicon from Microblogs by Combining Effects of Seed Words and Emoticons in a Heterogeneous Graph. HT 2015: 283-292 - [c25]Haishuai Wang, Peng Zhang, Ling Chen, Huan Liu, Chengqi Zhang:
Online diffusion source detection in social networks. IJCNN 2015: 1-8 - [c24]Weiqing Wang, Hongzhi Yin, Ling Chen, Yizhou Sun, Shazia Wasim Sadiq, Xiaofang Zhou:
Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation. KDD 2015: 1255-1264 - [c23]Bozhong Liu, Ling Chen, Chunyang Liu, Chengqi Zhang, Weidong Qiu:
RCP Mining: Towards the Summarization of Spatial Co-location Patterns. SSTD 2015: 451-469 - 2014
- [c22]Hongzhi Yin, Bin Cui, Ling Chen, Zhiting Hu, Zi Huang:
A temporal context-aware model for user behavior modeling in social media systems. SIGMOD Conference 2014: 1543-1554 - 2013
- [c21]Li Wan, Ling Chen, Chengqi Zhang:
Mining frequent serial episodes over uncertain sequence data. EDBT 2013: 215-226 - [c20]Li Wan, Ling Chen, Chengqi Zhang:
Mining Dependent Frequent Serial Episodes from Uncertain Sequence Data. ICDM 2013: 1211-1216 - [c19]Hongzhi Yin, Yizhou Sun, Bin Cui, Zhiting Hu, Ling Chen:
LCARS: a location-content-aware recommender system. KDD 2013: 221-229 - [c18]Chunyang Liu, Ling Chen, Chengqi Zhang:
Summarizing probabilistic frequent patterns: a fast approach. KDD 2013: 527-535 - [c17]Ling Chen, Chunyang Liu, Chengqi Zhang:
Mining Probabilistic Representative Frequent Patterns From Uncertain Data. SDM 2013: 73-81 - 2012
- [c16]Guodong Long, Ling Chen, Xingquan Zhu, Chengqi Zhang:
TCSST: transfer classification of short & sparse text using external data. CIKM 2012: 764-772 - 2011
- [c15]Ling Chen, Chengqi Zhang:
Semi-supervised Variable Weighting for Clustering. SDM 2011: 862-871 - 2010
- [c14]Jun Liu, Sha Sha, Qinghua Zheng, Ling Chen:
Ranking Difficulty of Knowledge Units Based on Learning Dependency. ICEBE 2010: 77-82 - 2009
- [c13]Ling Chen, Sourav S. Bhowmick:
In the Search of NECTARs from Evolutionary Trees. DASFAA 2009: 714-729 - [c12]Ling Chen, Phillip Wright, Wolfgang Nejdl:
Improving music genre classification using collaborative tagging data. WSDM 2009: 84-93 - 2008
- [c11]Ralf Krestel, Ling Chen:
The Art of Tagging: Measuring the Quality of Tags. ASWC 2008: 257-271 - [c10]Ling Chen, Yiqun Hu, Wolfgang Nejdl:
DECK: Detecting Events from Web Click-Through Data. ICDM 2008: 123-132 - [c9]Raluca Paiu, Ling Chen, Claudiu S. Firan, Wolfgang Nejdl:
PHAROS - Personalizing Users' Experience in Audio-Visual Online Spaces. PersDB 2008: 40-47 - [c8]Ling Chen, Yiqun Hu, Wolfgang Nejdl:
Using subspace analysis for event detection from web click-through data. WWW 2008: 1067-1068 - 2007
- [c7]Ling Chen, Sourav S. Bhowmick, Wolfgang Nejdl:
Mirror site maintenance based on evolution associations of web directories. WWW 2007: 1297-1298 - 2006
- [c6]Ling Chen, Sourav S. Bhowmick, Jinyan Li:
COWES: Clustering Web Users Based on Historical Web Sessions. DASFAA 2006: 541-556 - [c5]Ling Chen, Sourav S. Bhowmick, Jinyan Li:
Mining Temporal Indirect Associations. PAKDD 2006: 425-434 - 2005
- [c4]Ling Chen, Sourav S. Bhowmick, Liang-Tien Chia:
Mining Positive and Negative Association Rules from XML Query Patterns for Caching. DASFAA 2005: 736-747 - 2004
- [c3]Ling Chen, Sourav S. Bhowmick, Liang-Tien Chia:
Mining Maximal Frequently Changing Subtree Patterns from XML Documents. DaWaK 2004: 68-76 - [c2]Ling Chen, Sourav S. Bhowmick, Liang-Tien Chia:
VRules: an effective association-based classifier for videos. MMDB 2004: 85-93 - [c1]Ling Chen, Sourav S. Bhowmick, Liang-Tien Chia:
Mining Association Rules from Structural Deltas of Historical XML Documents. PAKDD 2004: 452-457
Editorship
- 2011
- [e2]Jie Tang, Irwin King, Ling Chen, Jianyong Wang:
Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Beijing, China, December 17-19, 2011, Proceedings, Part I. Lecture Notes in Computer Science 7120, Springer 2011, ISBN 978-3-642-25852-7 [contents] - [e1]Jie Tang, Irwin King, Ling Chen, Jianyong Wang:
Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Beijing, China, December 17-19, 2011, Proceedings, Part II. Lecture Notes in Computer Science 7121, Springer 2011, ISBN 978-3-642-25855-8 [contents]
Informal and Other Publications
- 2023
- [i19]Jiaxu Zhao, Meng Fang, Zijing Shi, Yitong Li, Ling Chen, Mykola Pechenizkiy:
CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models. CoRR abs/2305.11262 (2023) - [i18]Jiaxi Li, Guansong Pang, Ling Chen, Mohammad-Reza Namazi-Rad:
HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural Networks. CoRR abs/2308.14340 (2023) - [i17]Zihan Zhang, Meng Fang, Ling Chen, Mohammad-Reza Namazi-Rad, Jun Wang:
How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances. CoRR abs/2310.07343 (2023) - [i16]Zihan Zhang, Meng Fang, Ling Chen, Mohammad-Reza Namazi-Rad:
CITB: A Benchmark for Continual Instruction Tuning. CoRR abs/2310.14510 (2023) - [i15]Zihan Zhang, Meng Fang, Fanghua Ye, Ling Chen, Mohammad-Reza Namazi-Rad:
Turn-Level Active Learning for Dialogue State Tracking. CoRR abs/2310.14513 (2023) - 2022
- [i14]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, Chengqi Zhang:
Perceiving the World: Question-guided Reinforcement Learning for Text-based Games. CoRR abs/2204.09597 (2022) - [i13]Zihan Zhang, Meng Fang, Ling Chen, Mohammad-Reza Namazi-Rad:
Is Neural Topic Modelling Better than Clustering? An Empirical Study on Clustering with Contextual Embeddings for Topics. CoRR abs/2204.09874 (2022) - [i12]Shaoshen Wang, Yanbin Liu, Ling Chen, Chengqi Zhang:
Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection. CoRR abs/2205.14676 (2022) - 2021
- [i11]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Chengqi Zhang:
Generalization in Text-based Games via Hierarchical Reinforcement Learning. CoRR abs/2109.09968 (2021) - 2020
- [i10]Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Scott A. Sisson:
Recurrent Dirichlet Belief Networks for Interpretable Dynamic Relational Data Modelling. CoRR abs/2002.10235 (2020) - [i9]Xuhui Fan, Yaqiong Li, Ling Chen, Bin Li, Scott A. Sisson:
Smoothing Graphons for Modelling Exchangeable Relational Data. CoRR abs/2002.11159 (2020) - [i8]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, Chengqi Zhang:
Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games. CoRR abs/2010.11655 (2020) - 2019
- [i7]Xuhui Fan, Bin Li, Scott Anthony Sisson, Caoyuan Li, Ling Chen:
Scalable Deep Generative Relational Models with High-Order Node Dependence. CoRR abs/1911.01535 (2019) - 2018
- [i6]Bo Han, Ivor W. Tsang, Xiaokui Xiao, Ling Chen, Sai-Fu Fung, Celina Ping Yu:
Privacy-preserving Stochastic Gradual Learning. CoRR abs/1810.00383 (2018) - [i5]Wei Wu, Bin Li, Ling Chen, Junbin Gao, Chengqi Zhang:
A Review for Weighted MinHash Algorithms. CoRR abs/1811.04633 (2018) - 2017
- [i4]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang, Philip S. Yu:
Improved Consistent Weighted Sampling Revisited. CoRR abs/1706.01172 (2017) - 2016
- [i3]Bo Han, Ivor W. Tsang, Ling Chen:
On the Convergence of A Family of Robust Losses for Stochastic Gradient Descent. CoRR abs/1605.01623 (2016) - [i2]Xingzhong Du, Hongzhi Yin, Ling Chen, Yang Wang, Yi Yang, Xiaofang Zhou:
Exploiting Rich Contents for Personalized Video Recommendation. CoRR abs/1612.06935 (2016) - 2015
- [i1]Weiqing Wang, Hongzhi Yin, Ling Chen, Yizhou Sun, Shazia W. Sadiq, Xiaofang Zhou:
Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation. CoRR abs/1503.03650 (2015)
Coauthor Index
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last updated on 2024-04-25 05:55 CEST by the dblp team
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