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ORCIDHonghua Dai 0001
Person information
- affiliation: Deakin University, School of Information Technology, VIC, Australia
- affiliation: Zhengzhou University, Cooperative Innovation Center of Internet Healthcare, China
- affiliation (former): Monash University, Department of Computer Science, Clayton, VIC, Australia
- affiliation (PhD 1994): RMIT University, Department of Computer Science, Melbourne, VIC, Australia
Other persons with the same name
- Honghua Dai (aka: Hong-Hua Dai) — disambiguation page
- Honghua (Kathy) Dai (aka: Honghua Dai 0002) — Microsoft Corporation, Redmond, WA, USA (and 1 more)
- Honghua Dai 0003
![[0000-0001-7178-3960]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-7178-3960")
(aka: Hong-Hua Dai 0003) — Northwestern Polytechnical University, College of Astronautics, Xi'an, China (and 1 more)
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2020 – today
- 2022
[j18]Shuo Zhang, Jing Wang, Lulu Pei, Kai Liu, Yuan Gao, Hui Fang, Rui Zhang, Lu Zhao, Shilei Sun, Jun Wu, Bo Song, Honghua Dai, Runzhi Li, Yuming Xu:
Interpretable CNN for ischemic stroke subtype classification with active model adaptation. BMC Medical Informatics Decis. Mak. 22(1): 3 (2022)- [j17]Shuo Zhang, Jing Wang, Lulu Pei, Kai Liu, Yuan Gao, Hui Fang, Rui Zhang, Lu Zhao, Shilei Sun, Jun Wu, Bo Song, Honghua Dai, Runzhi Li, Yuming Xu:
Interpretability Analysis of One-Year Mortality Prediction for Stroke Patients Based on Deep Neural Network. IEEE J. Biomed. Health Informatics 26(4): 1903-1910 (2022) - [j16]Xueyuan Wang, Hongpo Zhang, Zongmin Wang, Yaqiong Qiao, Jiangtao Ma, Honghua Dai:
Con&Net: A Cross-Network Anchor Link Discovery Method Based on Embedding Representation. ACM Trans. Knowl. Discov. Data 16(2): 36:1-36:18 (2022) - 2021
- [j15]Haiyan Wang, Honghua Dai, Yanjie Zhou, Bing Zhou, Peng Lu, Hongpo Zhang, Zongmin Wang:
An effective feature extraction method based on GDS for atrial fibrillation detection. J. Biomed. Informatics 119: 103819 (2021) - [j14]Yange Sun, Honghua Dai:
Constructing accuracy and diversity ensemble using Pareto-based multi-objective learning for evolving data streams. Neural Comput. Appl. 33(11): 6119-6132 (2021) - 2020
- [j13]Yange Sun, Yi Sun, Honghua Dai:
Two-Stage Cost-Sensitive Learning for Data Streams With Concept Drift and Class Imbalance. IEEE Access 8: 191942-191955 (2020) - [c53]Xueli Duan, Shaobo Duan, Pei Jiang, Runzhi Li, Ye Zhang, Jingzhe Ma, Hongling Zhao, Honghua Dai:
An Ensemble Deep Learning Architecture for Multilabel Classification on TI-RADS. BIBM 2020: 576-582
2010 – 2019
- 2019
- [j12]Yang-Jie Cao, Li-Li Jia, Yong-Xia Chen, Nan Lin, Cong Yang, Bo Zhang, Zhi Liu, Xue-Xiang Li, Hong-Hua Dai:
Recent Advances of Generative Adversarial Networks in Computer Vision. IEEE Access 7: 14985-15006 (2019) - [j11]Runchuan Li, Xingjin Zhang, Honghua Dai, Bing Zhou, Zongmin Wang:
Interpretability Analysis of Heartbeat Classification Based on Heartbeat Activity's Global Sequence Features and BiLSTM-Attention Neural Network. IEEE Access 7: 109870-109883 (2019) - [j10]Xingjin Zhang, Runchuan Li, Honghua Dai, Yongpeng Liu, Bing Zhou, Zongmin Wang:
Localization of Myocardial Infarction With Multi-Lead Bidirectional Gated Recurrent Unit Neural Network. IEEE Access 7: 161152-161166 (2019) - 2018
- [j9]Yange Sun, Zhihai Wang, Yang Bai, Honghua Dai, Saeid Nahavandi:
A Classifier Graph Based Recurring Concept Detection and Prediction Approach. Comput. Intell. Neurosci. 2018: 4276291:1-4276291:13 (2018) - [j8]Muhammed J. A. Patwary, James N. K. Liu, Honghua Dai:
Recent advances of statistics in computational intelligence (RASCI). Int. J. Mach. Learn. Cybern. 9(1): 1-3 (2018) - [j7]Shigang Liu, Honghua Dai, Min Gan:
Information-decomposition-model-based missing value estimation for not missing at random dataset. Int. J. Mach. Learn. Cybern. 9(1): 85-95 (2018) - 2014
- [j6]Min Gan, Honghua Dai:
Detecting and monitoring abrupt emergences and submergences of episodes over data streams. Inf. Syst. 39: 277-289 (2014) - [c52]Shigang Liu, Honghua Dai:
Examination of Reliability of Missing Value Recovery in Data Mining. ICDM Workshops 2014: 306-313 - 2013
- [c51]Shigang Liu, Min Gan, Honghua Dai:
A hybrid approach to fuzzy risk analysis in stock market. FSKD 2013: 295-298 - [c50]Honghua Dai, Sarah Kenbl-Johnson:
An analytical study on causal induction. FSKD 2013: 908-913 - 2012
- [c49]Honghua Dai, Sarah Keble-Johnston, Min Gan:
Reliable Knowledge Discovery with a Minimal Causal Model Inducer. ICDM Workshops 2012: 629-634 - 2011
- [c48]Min Gan, Honghua Dai:
Quantitatively Evaluating the Effects of Price Promotions Using Data Mining. ISD 2011: 485-497 - [c47]Min Gan, Honghua Dai:
Fast Mining of Non-derivable Episode Rules in Complex Sequences. MDAI 2011: 67-78 - 2010
- [c46]Min Gan, Honghua Dai:
A Study on the Accuracy of Frequency Measures and Its Impact on Knowledge Discovery in Single Sequences. ICDM Workshops 2010: 859-866
2000 – 2009
- 2009
- [c45]Min Gan, Honghua Dai:
Efficient Mining of Top-k Breaker Emerging Subgraph Patterns from Graph Datasets. AusDM 2009: 183-192 - 2008
- [c44]Honghua Dai:
A Case Study on Classification Reliability. ICDM Workshops 2008: 69-73 - 2006
- [j5]Ling Zhuang, Honghua Dai:
Parameter Optimization of Kernel-based One-class Classifier on Imbalance Learning. J. Comput. 1(7): 32-40 (2006) - [c43]Yiqing Tu, Gang Li, Honghua Dai:
Integrating Local One-Class Classifiers for Image Retrieval. ADMA 2006: 213-222 - [c42]Ling Zhuang, Honghua Dai:
Parameter Estimation of One-Class SVM on Imbalance Text Classification. Canadian AI 2006: 538-549 - [c41]Xin Geng, Gang Li, Yangdong Ye, Yiqing Tu, Honghua Dai:
Abnormal Behavior Detection for Early Warning of Terrorist Attack. Australian Conference on Artificial Intelligence 2006: 1002-1009 - [c40]Ling Zhuang, Honghua Dai:
Reducing performance Bias for Unbalanced Text Mining. ICDM Workshops 2006: 770-774 - [c39]Honghua Dai:
A Study on Reliability in Graph Discovery. ICDM Workshops 2006: 775-779 - [c38]Xin Geng, Zhi-Hua Zhou, Yu Zhang, Gang Li, Honghua Dai:
Learning from facial aging patterns for automatic age estimation. ACM Multimedia 2006: 307-316 - [c37]Ling Zhuang, Honghua Dai:
Parameter Optimization of Kernel-Based One-Class Classifier on Imbalance Text Learning. PRICAI 2006: 434-443 - [c36]Xin Geng, Zhi-Hua Zhou, Honghua Dai:
Uncontrolled Face Recognition by Individual Stable Neural Network. PRICAI 2006: 553-562 - 2005
- [c35]Ling Zhuang, Honghua Dai, Xiaoshu Hang:
A Novel Field Learning Algorithm for Dual Imbalance Text Classification. FSKD (2) 2005: 39-48 - [c34]Gang Li, Honghua Dai:
Study of Ensemble Strategies in Discovering Linear Causal Models. FSKD (2) 2005: 368-377 - [c33]Xiaoshu Hang, Honghua Dai:
Applying both positive and negative selection to supervised learning for anomaly detection. GECCO 2005: 345-352 - [c32]Yiqing Tu, Gang Li, Honghua Dai:
Evolving Insight into High-Dimensional Data. ICIC (1) 2005: 465-474 - [c31]Yangdong Ye, Zundong Zhang, Limin Jia, Honghua Dai:
Research on train group operation model in RITS. ISADS 2005: 242-249 - [c30]James N. K. Liu, Honghua Dai, Lina Zhou:
Intelligent Financial News Digest System. KES (3) 2005: 112-120 - [c29]Xiaoshu Hang, James N. K. Liu, Yu Ren, Honghua Dai:
An Incremental FP-Growth Web Content Mining and Its Application in Preference Identification. KES (3) 2005: 121-127 - [c28]Yangdong Ye, Zundong Zhang, Honghua Dai, Limin Jia:
A Study of Train Group Operation Multi-agent Model Oriented to RITS. KES (1) 2005: 707-713 - [c27]Yuan Jiang, Jinjiang Ling, Gang Li, Honghua Dai, Zhi-Hua Zhou:
Dependency Bagging. RSFDGrC (1) 2005: 491-500 - 2004
- [j4]Gang Li, Honghua Dai:
What Will Affect Software Reuse: A Causal Model Analysis. Int. J. Softw. Eng. Knowl. Eng. 14(3): 351-364 (2004) - [j3]Honghua Dai, Geoffrey I. Webb:
Guest Editors' Introduction. Int. J. Softw. Eng. Knowl. Eng. 14(4): 365-368 (2004) - [j2]Honghua Dai, Wei Dai, Gang Li:
Software Warehouse: Its Design, Management And Application. Int. J. Softw. Eng. Knowl. Eng. 14(4): 395-406 (2004) - [c26]Ling Zhuang, Honghua Dai:
A Maximal Frequent Itemset Approach for Web Document Clustering. CIT 2004: 970-977 - [c25]Gulisong Nasierding, Yang Xiang, Honghua Dai:
Towards Extended Machine Translation Model for Next Generation World Wide Web. GCC 2004: 1017-1020 - [c24]Xiaoshu Hang, Honghua Dai:
Constructing Detectors in Schema Complementary Space for Anomaly Detection. GECCO (1) 2004: 275-286 - [c23]Xiaoshu Hang, Honghua Dai:
An Extended Negative Selection Algorithm for Anomaly Detection. PAKDD 2004: 245-254 - [c22]Honghua Dai, Gang Li, Zhi-Hua Zhou:
Ensembling MML Causal Discovery. PAKDD 2004: 260-271 - [c21]Zhi-Hua Zhou, Dan Wei, Gang Li, Honghua Dai:
On the Size of Training Set and the Benefit from Ensemble. PAKDD 2004: 298-307 - [c20]Gang Li, Honghua Dai, Yiqing Tu:
Identifying Markov Blankets Using Lasso Estimation. PAKDD 2004: 308-318 - [c19]Gang Li, Honghua Dai, Yiqing Tu, Tarkan Kurt:
Accelerating Linear Causal Model Discovery Using Hoeffding Bounds. PRICAI 2004: 201-210 - [c18]Xiaoshu Hang, Honghua Dai:
Combining Extension Matrix and Integer Programming for Optimal Concept Learning. PRICAI 2004: 352-360 - [c17]Gang Li, Honghua Dai:
The Discovery of Generalized Causal Models with Mixed Variables Using MML Criterion. SDM 2004: 487-491 - [c16]Xiaoshu Hang, Honghua Dai:
An Immune Network Approach for Web Document Clustering. Web Intelligence 2004: 278-284 - [e1]Honghua Dai, Ramakrishnan Srikant, Chengqi Zhang:
Advances in Knowledge Discovery and Data Mining, 8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004, Proceedings. Lecture Notes in Computer Science 3056, Springer 2004, ISBN 3-540-22064-X [contents] - 2003
- [c15]Xiaoshu Hang, Honghua Dai:
An Optimal Strategy for Extracting Probabilistic Rules by Combining Rough Sets and Genetic Algorithm. Discovery Science 2003: 153-165 - [c14]Xiaoshu Hang, Honghua Dai, E. Lanham:
Mining Sequential Causal Patterns with User-Specified Skeletons in Multi-Sequence of Event Data. HIS 2003: 702-711 - [c13]Xiaoshu Hang, Honghua Dai, Youhua Zhang:
An Incremental FP-Growth Approach for Web-Content Based Dynamic Data Mining. IC-AI 2003: 101-107 - [c12]Xiaoshu Hang, Honghua Dai, Youhua Zhang:
A Web content based data mining for car consumption preference in China. IRI 2003: 235-242 - 2002
- [c11]Honghua Dai, Gang Li, Yiqing Tu:
An Empirical Study of Encoding Schemes and Search Strategies in Discovering Causal Networks. ECML 2002: 48-59 - [c10]Gang Li, Honghua Dai, Yiqing Tu:
Linear Causal Model Discovery Using the MML criterion. ICDM 2002: 274-281 - [c9]Honghua Dai, Gang Li:
An Improved Approach for the Discovery of Causal Models via MML. PAKDD 2002: 304-315 - 2001
- [c8]Honghua Dai, Xiaoshu Hang, Gang Li:
Inexact Field Learning: An Approach to Induce High Quality Rules from Low Quality Data. ICDM 2001: 586-588 - [c7]Gang Li, Fu Tong, Honghua Dai:
Evolutionary Structure Learning Algorithm for Bayesian Network and Penalized Mutual Information Metric. ICDM 2001: 615-616
1990 – 1999
- 1999
- [c6]Honghua Dai:
A Minimal Causal Model Learner. PAKDD 1999: 400-408 - 1998
- [j1]Bavy Li, James N. K. Liu, Honghua Dai:
Forecasting from Low Quality Data with Applications in Weather Forecasting. Informatica (Slovenia) 22(3) (1998) - [c5]Honghua Dai:
Trend Directed Learning: A Case Study. PAKDD 1998: 61-71 - 1997
- [c4]Honghua Dai, Kevin B. Korb, Chris S. Wallace, Xindong Wu:
A Study of Causal Discovery With Weak Links and Small Samples. IJCAI 1997: 1304-1309 - 1996
- [c3]Honghua Dai, Kevin B. Korb, Chris S. Wallace:
The discovery of causal models with small samples. ANZIIS 1996: 27-30 - [c2]Honghua Dai, James N. K. Liu, Victor Ciesielski:
An analysis of criteria for the evaluation of learning performance. ANZIIS 1996: 84-87 - [c1]Chris S. Wallace, Kevin B. Korb, Honghua Dai:
Causal Discovery via MML. ICML 1996: 516-524
Coauthor Index
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