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Yun Sing Koh
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2020 – today
- 2024
- [j32]Jiachen Lyu, Katharina Dost, Yun Sing Koh, Jörg Wicker:
Regional bias in monolingual English language models. Mach. Learn. 113(9): 6663-6696 (2024) - [c106]Di Zhao, Yun Sing Koh, Gillian Dobbie, Hongsheng Hu, Philippe Fournier-Viger:
Symmetric Self-Paced Learning for Domain Generalization. AAAI 2024: 16961-16969 - [c105]Thomas Bailie, Yun Sing Koh, Neelesh Rampal, Peter B. Gibson:
Quantile-Regression-Ensemble: A Deep Learning Algorithm for Downscaling Extreme Precipitation. AAAI 2024: 21914-21922 - [c104]Wernsen Wong, Yun Sing Koh, Gillian Dobbie:
Learning After Learning: Positive Backward Transfer in Continual Learning. ECAI 2024: 2019-2026 - [c103]Olivier Graffeuille, Yun Sing Koh, Jörg Wicker, Moritz K. Lehmann:
Remote Sensing for Water Quality: A Multi-Task, Metadata-Driven Hypernetwork Approach. IJCAI 2024: 7287-7295 - [c102]Yun Sing Koh, Albert Bifet, Karin R. Bryan, Guilherme Weigert Cassales, Olivier Graffeuille, Nick Jin Sean Lim, Phil Mourot, Ding Ning, Bernhard Pfahringer, Varvara Vetrova, Heitor Murilo Gomes:
Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme. IJCAI 2024: 7314-7322 - [c101]Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet, Yun Sing Koh:
Recurrent Concept Drifts on Data Streams. IJCAI 2024: 8029-8037 - [c100]Jack Julian, Yun Sing Koh, Albert Bifet:
Sketch-Based Replay Projection for Continual Learning. KDD 2024: 1325-1335 - [c99]Bowen Chen, Yun Sing Koh, Gillian Dobbie:
SSAT-Adapter: Enhancing Vision-Language Model Few-shot Learning with Auxiliary Tasks. ACM Multimedia 2024: 1004-1013 - [c98]Bowen Chen, Gillian Dobbie, Neelesh Rampal, Yun Sing Koh:
Unveiling Climate Drivers via Feature Importance Shift Analysis in New Zealand. WWW 2024: 4595-4606 - [e5]Diana Benavides-Prado, Sarah M. Erfani, Philippe Fournier-Viger, Yee Ling Boo, Yun Sing Koh:
Data Science and Machine Learning - 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11-13, 2023, Proceedings. Communications in Computer and Information Science 1943, Springer 2024, ISBN 978-981-99-8695-8 [contents] - [i9]Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang:
Privacy-Preserving Low-Rank Adaptation for Latent Diffusion Models. CoRR abs/2402.11989 (2024) - [i8]Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet:
A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams. CoRR abs/2408.09324 (2024) - [i7]Olivier Graffeuille, Yun Sing Koh, Jörg S. Wicker, Moritz K. Lehmann:
Enabling Asymmetric Knowledge Transfer in Multi-Task Learning with Self-Auxiliaries. CoRR abs/2410.15875 (2024) - [i6]Yihao Wu, Di Zhao, Jingfeng Zhang, Yun Sing Koh:
An Individual Identity-Driven Framework for Animal Re-Identification. CoRR abs/2410.22927 (2024) - 2023
- [j31]Qifan Wang, Lei Zhou, Jianli Bai, Yun Sing Koh, Shujie Cui, Giovanni Russello:
HT2ML: An efficient hybrid framework for privacy-preserving Machine Learning using HE and TEE. Comput. Secur. 135: 103509 (2023) - [j30]Peter Devine, Yun Sing Koh, Kelly Blincoe:
Evaluating software user feedback classifier performance on unseen apps, datasets, and metadata. Empir. Softw. Eng. 28(1): 26 (2023) - [j29]Sijie Zhuo, Robert Biddle, Yun Sing Koh, Danielle M. Lottridge, Giovanni Russello:
SoK: Human-centered Phishing Susceptibility. ACM Trans. Priv. Secur. 26(3): 24:1-24:27 (2023) - [j28]Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet:
Combining Diverse Meta-Features to Accurately Identify Recurring Concept Drift in Data Streams. ACM Trans. Knowl. Discov. Data 17(8): 107:1-107:36 (2023) - [c97]Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet:
FALL: A Modular Adaptive Learning Platform for Streaming Data. ICDE 2023: 3619-3622 - [c96]Aaron Keesing, Yun Sing Koh, Vithya Yogarajan, Michael Witbrock:
Emotion Recognition ToolKit (ERTK): Standardising Tools For Emotion Recognition Research. ACM Multimedia 2023: 9693-9696 - [c95]Sijie Zhuo, Robert Biddle, Lucas Betts, Nalin A. G. Arachchilage, Yun Sing Koh, Danielle M. Lottridge, Giovanni Russello:
A Large-Scale Study of Device and Link Presentation in Email Phishing Susceptibility. OZCHI 2023: 78-85 - [c94]Wernsen Wong, Yun Sing Koh, Gillian Dobbie:
Using Flexible Memories to Reduce Catastrophic Forgetting. PAKDD (2) 2023: 219-230 - [i5]Sijie Zhuo, Robert Biddle, Lucas Betts, Nalin Asanka Gamagedara Arachchilage, Yun Sing Koh, Danielle M. Lottridge, Giovanni Russello:
What You See is Not What You Get: The Role of Email Presentation in Phishing Susceptibility. CoRR abs/2304.00664 (2023) - [i4]Qifan Wang, Shujie Cui, Lei Zhou, Ye Dong, Jianli Bai, Yun Sing Koh, Giovanni Russello:
GTree: GPU-Friendly Privacy-preserving Decision Tree Training and Inference. CoRR abs/2305.00645 (2023) - 2022
- [j27]Ocean Wu, Yun Sing Koh, Gillian Dobbie, Thomas Lacombe:
Probabilistic exact adaptive random forest for recurrent concepts in data streams. Int. J. Data Sci. Anal. 13(1): 17-32 (2022) - [j26]Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson:
Analyzing and repairing concept drift adaptation in data stream classification. Mach. Learn. 111(10): 3489-3523 (2022) - [c93]Olivier Graffeuille, Yun Sing Koh, Jörg Wicker, Moritz K. Lehmann:
Semi-supervised Conditional Density Estimation with Wasserstein Laplacian Regularisation. AAAI 2022: 6746-6754 - [c92]Bowen Chen, Yun Sing Koh, Ben Halstead:
Active Learning Using Difficult Instances. AI 2022: 747-760 - [c91]Bowen Chen, Yun Sing Koh, Ben Halstead:
Measuring Difficulty of Learning Using Ensemble Methods. AusDM 2022: 28-42 - [c90]Krithik Ramesh, Yun Sing Koh:
Investigation of Explainability Techniques for Multimodal Transformers. AusDM 2022: 90-98 - [c89]Bowen Chen, Yun Sing Koh, Gillian Dobbie, Ocean Wu, Guy Coulson, Gustavo Olivares:
Online Air Pollution Inference using Concept Recurrence and Transfer Learning. DSAA 2022: 1-10 - [c88]Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet:
A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams. DSAA 2022: 1-10 - [c87]Ocean Wu, Yun Sing Koh, Gillian Dobbie, Thomas Lacombe:
Cost-Effective Transfer Learning for Data Streams. ICDM 2022: 1233-1238 - [c86]Di Zhao, Yun Sing Koh, Philippe Fournier-Viger:
Measuring Drift Severity by Tree Structure Classifiers. IJCNN 2022: 1-8 - [c85]Peter Devine, James Tizard, Hechen Wang, Yun Sing Koh, Kelly Blincoe:
What's Inside a Cluster of Software User Feedback: A Study of Characterisation Methods. RE 2022: 189-200 - [e4]Laurence A. F. Park, Heitor Murilo Gomes, Maryam Gholami Doborjeh, Yee Ling Boo, Yun Sing Koh, Yanchang Zhao, Graham J. Williams, Simeon Simoff:
Data Mining - 20th Australasian Conference, AusDM 2022, Western Sydney, Australia, December 12-15, 2022, Proceedings. Communications in Computer and Information Science 1741, Springer 2022, ISBN 978-981-19-8745-8 [contents] - [i3]Sijie Zhuo, Robert Biddle, Yun Sing Koh, Danielle M. Lottridge, Giovanni Russello:
SoK: Human-Centered Phishing Susceptibility. CoRR abs/2202.07905 (2022) - 2021
- [j25]Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet:
Recurring concept memory management in data streams: exploiting data stream concept evolution to improve performance and transparency. Data Min. Knowl. Discov. 35(3): 796-836 (2021) - [c84]Ocean Wu, Yun Sing Koh, Gillian Dobbie, Thomas Lacombe:
Transfer Learning with Adaptive Online TrAdaBoost for Data Streams. ACML 2021: 1017-1032 - [c83]Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson:
Analyzing and Repairing Concept Drift Adaptation in Data Stream Classification. DSAA 2021: 1-2 - [c82]Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet, Russel Pears:
Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information. ICDE 2021: 1056-1067 - [c81]Andrew Chester, Yun Sing Koh, Junjae Lee:
Understanding the Effects of Mitigation on De-identified Data. IEA/AIE (1) 2021: 133-144 - [c80]Callum Cory, Diana Benavides Prado, Yun Sing Koh:
Continual Correction of Errors Using Smart Memory Replay. IJCNN 2021: 1-8 - [c79]Thomas Lacombe, Yun Sing Koh, Gillian Dobbie, Ocean Wu:
A Meta-Learning Approach for Automated Hyperparameter Tuning in Evolving Data Streams. IJCNN 2021: 1-8 - [c78]Ocean Wu, Yun Sing Koh, Gillian Dobbie, Thomas Lacombe:
Nacre: Proactive Recurrent Concept Drift Detection in Data Streams. IJCNN 2021: 1-8 - [c77]Aaron Keesing, Yun Sing Koh, Michael Witbrock:
Acoustic Features and Neural Representations for Categorical Emotion Recognition from Speech. Interspeech 2021: 3415-3419 - [c76]Peter Devine, Yun Sing Koh, Kelly Blincoe:
Evaluating Unsupervised Text Embeddings on Software User Feedback. RE Workshops 2021: 87-95 - [e3]James Bailey, Pauli Miettinen, Yun Sing Koh, Dacheng Tao, Xindong Wu:
IEEE International Conference on Data Mining, ICDM 2021, Auckland, New Zealand, December 7-10, 2021. IEEE 2021, ISBN 978-1-6654-2398-4 [contents] - [i2]Peter Devine, Yun Sing Koh, Kelly Blincoe:
Evaluating Software User Feedback Classifiers on Unseen Apps, Datasets, and Metadata. CoRR abs/2112.13497 (2021) - 2020
- [j24]Diana Benavides Prado, Yun Sing Koh, Patricia Riddle:
Towards Knowledgeable Supervised Lifelong Learning Systems. J. Artif. Intell. Res. 68: 159-224 (2020) - [j23]Sijie Zhuo, Lucas Sherlock, Gillian Dobbie, Yun Sing Koh, Giovanni Russello, Danielle M. Lottridge:
Real-time Smartphone Activity Classification Using Inertial Sensors - Recognition of Scrolling, Typing, and Watching Videos While Sitting or Walking. Sensors 20(3): 655 (2020) - [c75]Di Zhao, Yun Sing Koh:
Feature Drift Detection in Evolving Data Streams. DEXA (2) 2020: 335-349 - [c74]Balkaran Singh, Quan Sun, Yun Sing Koh, Junjae Lee, Edmond Zhang:
Detecting Protected Health Information with an Incremental Learning Ensemble: A Case Study on New Zealand Clinical Text. DSAA 2020: 719-728 - [c73]Shuxiang Zhang, David Tse Jung Huang, Gillian Dobbie, Yun Sing Koh:
SLED: Semi-supervised Locally-weighted Ensemble Detector. ICDE 2020: 1838-1841 - [c72]Ocean Wu, Yun Sing Koh, Giovanni Russello:
GPU-based State Adaptive Random Forest for Evolving Data Streams. IJCNN 2020: 1-8 - [c71]Ocean Wu, Yun Sing Koh, Gillian Dobbie, Thomas Lacombe:
PEARL: Probabilistic Exact Adaptive Random Forest with Lossy Counting for Data Streams. PAKDD (2) 2020: 17-30 - [c70]Hamish Huggard, Yun Sing Koh, Gillian Dobbie, Edmond Zhang:
Detecting Concept Drift In Medical Triage. SIGIR 2020: 1733-1736 - [c69]Andrew Chester, Yun Sing Koh, Jörg Wicker, Quan Sun, Junjae Lee:
Balancing Utility and Fairness against Privacy in Medical Data. SSCI 2020: 1226-1233
2010 – 2019
- 2019
- [j22]Ranran Bian, Yun Sing Koh, Gillian Dobbie, Anna Divoli:
Identifying Top-k Nodes in Social Networks: A Survey. ACM Comput. Surv. 52(1): 22:1-22:33 (2019) - [j21]Robert Anderson, Yun Sing Koh, Gillian Dobbie, Albert Bifet:
Recurring concept meta-learning for evolving data streams. Expert Syst. Appl. 138 (2019) - [j20]Philippe Fournier-Viger, Yimin Zhang, Jerry Chun-Wei Lin, Hamido Fujita, Yun Sing Koh:
Mining local and peak high utility itemsets. Inf. Sci. 481: 344-367 (2019) - [c68]Alex Yuxuan Peng, Yun Sing Koh, Patricia Riddle, Bernhard Pfahringer:
Investigating the effect of novel classes in semi-supervised learning. ACML 2019: 615-630 - [c67]Ian Shane Wong, Gillian Dobbie, Yun Sing Koh:
Items2Data: Generating Synthetic Boolean Datasets from Itemsets. ADC 2019: 79-90 - [c66]Hamish Huggard, Aaron Zhang, Edmond Zhang, Yun Sing Koh:
Feature Importance for Biomedical Named Entity Recognition. Australasian Conference on Artificial Intelligence 2019: 406-417 - [c65]Wernsen Wong, Yun Sing Koh, Gillian Dobbie:
Using Transfer Learning to Detect Phishing in Countries with a Small Population. AusDM 2019: 129-140 - [c64]Robert Anderson, Yun Sing Koh, Gillian Dobbie:
Classifying Imbalanced Road Accident Data Using Recurring Concept Drift. AusDM 2019: 143-155 - [c63]Diana Benavides Prado, Yun Sing Koh, Patricia Riddle:
Selective Hypothesis Transfer for Lifelong Learning. IJCNN 2019: 1-10 - [c62]Feiyang Tang, David Tse Jung Huang, Yun Sing Koh, Philippe Fournier-Viger:
Adaptive Self-Sufficient Itemset Miner for Transactional Data Streams. PRICAI (2) 2019: 419-430 - [c61]Xiaolong Huang, Edmond Zhang, Yun Sing Koh:
Supervised Clinical Abbreviations Detection and Normalisation Approach. PRICAI (3) 2019: 691-703 - [c60]Ranran Bian, Yun Sing Koh, Gillian Dobbie, Anna Divoli:
Network Embedding and Change Modeling in Dynamic Heterogeneous Networks. SIGIR 2019: 861-864 - [e2]Md. Rafiqul Islam, Yun Sing Koh, Yanchang Zhao, Warwick Graco, David Stirling, Chang-Tsun Li, Md Zahidul Islam:
Data Mining - 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, Australia, November 28-30, 2018, Revised Selected Papers. Communications in Computer and Information Science 996, Springer 2019, ISBN 978-981-13-6660-4 [contents] - [i1]Robert Anderson, Yun Sing Koh, Gillian Dobbie, Albert Bifet:
Recurring Concept Meta-learning for Evolving Data Streams. CoRR abs/1905.08848 (2019) - 2018
- [j19]Prabha Rajagopal, Sri Devi Ravana, Yun Sing Koh, Vimala Balakrishnan:
Evaluating the effectiveness of information retrieval systems using effort-based relevance judgment. Aslib J. Inf. Manag. 71(1): 2-17 (2018) - [c59]Philippe Fournier-Viger, Yimin Zhang, Jerry Chun-Wei Lin, Yun Sing Koh:
Discovering High Utility Change Points in Customer Transaction Data. ADMA 2018: 392-402 - [c58]Ranran Bian, Yun Sing Koh, Gillian Dobbie, Anna Divoli:
OHC: Uncovering Overlapping Heterogeneous Communities. Australasian Conference on Artificial Intelligence 2018: 193-205 - [c57]Robert Anderson, Yun Sing Koh, Gillian Dobbie:
Lift-Per-Drift: An Evaluation Metric for Classification Frameworks with Concept Drift Detection. Australasian Conference on Artificial Intelligence 2018: 630-642 - [c56]Moana Stirling, Yun Sing Koh, Philippe Fournier-Viger, Sri Devi Ravana:
Concept Drift Detector Selection for Hoeffding Adaptive Trees. Australasian Conference on Artificial Intelligence 2018: 730-736 - [c55]Hamish Huggard, Yun Sing Koh, Patricia Riddle, Gustavo Olivares:
Predicting Air Quality from Low-Cost Sensor Measurements. AusDM 2018: 94-106 - [c54]David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie:
Interpreting Intermittent Bugs in Mozilla Applications Using Change Angle. AusDM 2018: 318-330 - [c53]Philippe Fournier-Viger, Yimin Zhang, Jerry Chun-Wei Lin, Hamido Fujita, Yun Sing Koh:
Mining Local High Utility Itemsets. DEXA (2) 2018: 450-460 - [c52]Yun Sing Koh, David Tse Jung Huang, Chris Pearce, Gillian Dobbie:
Volatility Drift Prediction for Transactional Data Streams. ICDM 2018: 1091-1096 - [c51]Robert Anderson, Yun Sing Koh, Gillian Dobbie:
Predicting Concept Drift in Data Streams Using Metadata Clustering. IJCNN 2018: 1-8 - [c50]Alex Yuxuan Peng, Yun Sing Koh, Patricia Riddle, Bernhard Pfahringer:
Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems. ECML/PKDD (1) 2018: 410-425 - [c49]Jiazhen Chen, Gillian Dobbie, Yun Sing Koh, Elizabeth Somervell, Gustavo Olivares:
Vehicle emission prediction using remote sensing data and machine learning techniques. SAC 2018: 444-451 - 2017
- [j18]Parnia Samimi, Sri Devi Ravana, William Webber, Yun Sing Koh:
Effects of objective and subjective competence on the reliability of crowdsourced relevance judgments. Inf. Res. 22(1) (2017) - [c48]Diana Benavides Prado, Yun Sing Koh, Patricia Riddle:
AccGenSVM: Selectively Transferring from Previous Hypotheses. IJCAI 2017: 1440-1446 - [c47]Ruolin Jia, Yun Sing Koh, Gillian Dobbie:
Volatility Adaptive Classifier System. PAKDD (1) 2017: 122-134 - [c46]Alex Yuxuan Peng, Yun Sing Koh, Patricia Riddle:
mHUIMiner: A Fast High Utility Itemset Mining Algorithm for Sparse Datasets. PAKDD (2) 2017: 196-207 - 2016
- [j17]Parnia Samimi, Sri Devi Ravana, Yun Sing Koh:
Effect of verbal comprehension skill and self-reported features on reliability of crowdsourced relevance judgments. Comput. Hum. Behav. 64: 793-804 (2016) - [j16]Yun Sing Koh, Sri Devi Ravana:
Unsupervised Rare Pattern Mining: A Survey. ACM Trans. Knowl. Discov. Data 10(4): 45:1-45:29 (2016) - [c45]Robert Anderson, Yun Sing Koh, Gillian Dobbie:
CPF: Concept Profiling Framework for Recurring Drifts in Data Streams. Australasian Conference on Artificial Intelligence 2016: 203-214 - [c44]Kylie Chen, Yun Sing Koh, Patricia Riddle:
Proactive drift detection: Predicting concept drifts in data streams using probabilistic networks. IJCNN 2016: 780-787 - [c43]Yun Sing Koh:
CD-TDS: Change detection in transactional data streams for frequent pattern mining. IJCNN 2016: 1554-1561 - [c42]Se Yeong Jeong, Yun Sing Koh, Gillian Dobbie:
Phishing Detection on Twitter Streams. PAKDD Workshops 2016: 141-153 - 2015
- [j15]Russel Pears, Songwut Pisalpanus, Yun Sing Koh:
A graph based approach to inferring item weights for pattern mining. Expert Syst. Appl. 42(1): 451-461 (2015) - [j14]David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie:
Rare Pattern Mining from Data Streams Using SRP-Tree and Its Variants. Trans. Large Scale Data Knowl. Centered Syst. 21: 140-160 (2015) - [c41]Kylie Chen, Yun Sing Koh, Patricia Riddle:
Tracking Drift Severity in Data Streams. Australasian Conference on Artificial Intelligence 2015: 96-108 - [c40]Mohammad Abdullatif, Yun Sing Koh, Gillian Dobbie:
Unsupervised Semantic and Syntactic Based Classification of Scientific Citations. DaWaK 2015: 28-39 - [c39]Yun Sing Koh, Russel Pears:
HI-Tree: Mining High Influence Patterns Using External and Internal Utility Values. DaWaK 2015: 43-56 - [c38]Robert Anderson, Yun Sing Koh:
StreamXM: An Adaptive Partitional Clustering Solution for Evolving Data Streams. DaWaK 2015: 270-282 - [c37]David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Albert Bifet:
Drift Detection Using Stream Volatility. ECML/PKDD (1) 2015: 417-432 - 2014
- [j13]Sidney Tsang, Yun Sing Koh, Gillian Dobbie, Shafiq Alam:
Detecting online auction shilling frauds using supervised learning. Expert Syst. Appl. 41(6): 3027-3040 (2014) - [j12]Yun Sing Koh, Russel Pears:
Efficient negative association rule mining based on chance thresholds. Intell. Data Anal. 18(2): 243-260 (2014) - [j11]Sidney Tsang, Yun Sing Koh, Gillian Dobbie, Shafiq Alam:
SPAN: Finding collaborative frauds in online auctions. Knowl. Based Syst. 71: 389-408 (2014) - [j10]Russel Pears, Sripirakas Sakthithasan, Yun Sing Koh:
Detecting concept change in dynamic data streams - A sequential approach based on reservoir sampling. Mach. Learn. 97(3): 259-293 (2014) - [j9]Shafiq Alam, Gillian Dobbie, Yun Sing Koh, Patricia Riddle, Saeed Ur Rehman:
Research on particle swarm optimization based clustering: A systematic review of literature and techniques. Swarm Evol. Comput. 17: 1-13 (2014) - [j8]Shafiq Alam, Gillian Dobbie, Yun Sing Koh, Patricia Riddle:
Web usage mining based recommender systems using implicit heterogeneous data: - A Particle Swarm Optimization based clustering approach. Web Intell. Agent Syst. 12(4): 389-409 (2014) - [c36]Shafiq Alam, Gillian Dobbie, Yun Sing Koh, Patricia Riddle:
Web bots detection using Particle Swarm Optimization based clustering. IEEE Congress on Evolutionary Computation 2014: 2955-2962 - [c35]Timothy D. Robinson, David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie:
Drift Detector for Memory-Constrained Environments. DaWaK 2014: 414-425 - [c34]David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Russel Pears:
Detecting Volatility Shift in Data Streams. ICDM 2014: 863-868 - [c33]Wei Zhou, Junhao Wen, Yun Sing Koh, Shafiq Alam, Gillian Dobbie:
Attack detection in recommender systems based on target item analysis. IJCNN 2014: 332-339 - [c32]