Koh, Yun Sing

23 publications

IJCAI 2025 Balancing Invariant and Specific Knowledge for Domain Generalization with Online Knowledge Distillation Di Zhao, Jingfeng Zhang, Hongsheng Hu, Philippe Fournier-Viger, Gillian Dobbie, Yun Sing Koh

IJCAI 2025 CABIN: Debiasing Vision-Language Models Using Backdoor Adjustments Bo Pang, Tingrui Qiao, Caroline Walker, Chris Cunningham, Yun Sing Koh

ICCV 2025 GloPER: Unsupervised Animal Pattern Extraction from Local Reconstruction Bowen Chen, Yun Sing Koh, Gillian Dobbie

ECML-PKDD 2025 Longitudinal Surveys Are Texts: LLM-Enhanced Analysis of School Attendance in New Zealand Tingrui Qiao, Caroline Walker, Chris Cunningham, Adam Jang-Jones, Susan M. B. Morton, Kane Meissel, Yun Sing Koh

ECML-PKDD 2025 Machine Learning for Data Streams with CapyMOA Yibin Sun, Heitor Murilo Gomes, Anton Lee, Nuwan Gunasekara, Guilherme Weigert Cassales, Justin Liu, Marco Heyden, Vítor Cerqueira, Maroua Bahri, Yun Sing Koh, Bernhard Pfahringer, Albert Bifet

AAAI 2025 Privacy-Preserving Low-Rank Adaptation Against Membership Inference Attacks for Latent Diffusion Models Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang

ICLRW 2025 Understanding School Attendance Through Multimodal Modelling of Student Narratives Tingrui Qiao, Caroline Walker, Chris W Cunningham, Adam Jang-Jones, Susan Mary Bennett Morton, Kane Meissel, Yun Sing Koh

AAAI 2024 Quantile-Regression-Ensemble: A Deep Learning Algorithm for Downscaling Extreme Precipitation Thomas Bailie, Yun Sing Koh, Neelesh Rampal, Peter B. Gibson

IJCAI 2024 Recurrent Concept Drifts on Data Streams Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet, Yun Sing Koh

MLJ 2024 Regional Bias in Monolingual English Language Models Jiachen Lyu, Katharina Dost, Yun Sing Koh, Jörg Wicker

IJCAI 2024 Remote Sensing for Water Quality: A Multi-Task, Metadata-Driven Hypernetwork Approach Olivier Graffeuille, Yun Sing Koh, Jörg Wicker, Moritz K. Lehmann

AAAI 2024 Symmetric Self-Paced Learning for Domain Generalization Di Zhao, Yun Sing Koh, Gillian Dobbie, Hongsheng Hu, Philippe Fournier-Viger

IJCAI 2024 Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme 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

ICLRW 2024 Towards Personalized AI: Early-Stopping Low-Rank Adaptation of Foundation Models Zihao Luo, Di Wang, Yun Sing Koh, Jingfeng Zhang

MLJ 2022 Analyzing and Repairing Concept Drift Adaptation in Data Stream Classification Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson

AAAI 2022 Semi-Supervised Conditional Density Estimation with Wasserstein Laplacian Regularisation Olivier Graffeuille, Yun Sing Koh, Jörg Wicker, Moritz K. Lehmann

ACML 2021 Transfer Learning with Adaptive Online TrAdaBoost for Data Streams Ocean Wu, Yun Sing Koh, Gillian Dobbie, Thomas Lacombe

JAIR 2020 Towards Knowledgeable Supervised Lifelong Learning Systems Diana Benavides Prado, Yun Sing Koh, Patricia Riddle

ACML 2019 Investigating the Effect of Novel Classes in Semi-Supervised Learning Alex Yuxuan Peng, Yun Sing Koh, Patricia Riddle, Bernhard Pfahringer

ECML-PKDD 2018 Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems Alex Yuxuan Peng, Yun Sing Koh, Patricia Riddle, Bernhard Pfahringer

IJCAI 2017 AccGenSVM: Selectively Transferring from Previous Hypotheses Diana Benavides Prado, Yun Sing Koh, Patricia Riddle

ECML-PKDD 2015 Drift Detection Using Stream Volatility David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Albert Bifet

MLJ 2014 Detecting Concept Change in Dynamic Data Streams - A Sequential Approach Based on Reservoir Sampling Russel Pears, Sripirakas Sakthithasan, Yun Sing Koh