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2024 Journal Article A boosting framework for positive-unlabeled learningZhao, Yawen, Zhang, Mingzhe, Zhang, Chenhao, Chen, Weitong, Ye, Nan and Xu, Miao (2024). A boosting framework for positive-unlabeled learning. Statistics and Computing, 35 (1) 2. doi: 10.1007/s11222-024-10529-y |
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2024 Journal Article Structured neural networks for CPUE standardization: A case study of the blue endeavour prawn in Australia's Northern Prawn FisheryLei, Yeming, Zhou, Shijie and Ye, Nan (2024). Structured neural networks for CPUE standardization: A case study of the blue endeavour prawn in Australia's Northern Prawn Fishery. Fisheries Research, 279 107140, 107140. doi: 10.1016/j.fishres.2024.107140 |
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2024 Journal Article Eliciting patient preferences and predicting behaviour using Inverse Reinforcement Learning for telehealth use in outpatient clinicsSnoswell, Aaron J., Snoswell, Centaine L. and Ye, Nan (2024). Eliciting patient preferences and predicting behaviour using Inverse Reinforcement Learning for telehealth use in outpatient clinics. Frontiers in Digital Health, 6 1384248. doi: 10.3389/fdgth.2024.1384248 |
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2024 Journal Article Spatial-temporal neural networks for catch rate standardization and fish distribution modelingLei, Yeming, Zhou, Shijie and Ye, Nan (2024). Spatial-temporal neural networks for catch rate standardization and fish distribution modeling. Fisheries Research, 278 107097, 107097. doi: 10.1016/j.fishres.2024.107097 |
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2024 Journal Article Adaptive discretization using Voronoi trees for continuous pOMDPsHoerger, Marcus, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2024). Adaptive discretization using Voronoi trees for continuous pOMDPs. The International Journal of Robotics Research, 43 (9), 1283-1298. doi: 10.1177/02783649231188984 |
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2024 Conference Publication Fast controllable diffusion models for undersampled MRI reconstructionJiang, Wei, Xiong, Zhuang, Liu, Feng, Ye, Nan and Sun, Hongfu (2024). Fast controllable diffusion models for undersampled MRI reconstruction. 2024 IEEE International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 27-30 May 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/isbi56570.2024.10635891 |
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2024 Conference Publication Robust loss functions for training decision trees with noisy labelsWilton, Jonathan and Ye, Nan (2024). Robust loss functions for training decision trees with noisy labels. Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24), Vancouver, BC, Canada, 20 - 28 February 2024. Washington, DC, United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v38i14.29516 |
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2024 Conference Publication A surprisingly simple continuous-action POMDP solver: lazy cross-entropy search over policy treesHoerger, Marcus, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2024). A surprisingly simple continuous-action POMDP solver: lazy cross-entropy search over policy trees. 38th AAAI Conference on Artificial Intelligence (AAAI) / 36th Conference on Innovative Applications of Artificial Intelligence / 14th Symposium on Educational Advances in Artificial Intelligence, Vancouver, Canada, 20-27 February 2024. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v38i18.29992 |
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2023 Journal Article Blockwise acceleration of alternating least squares for canonical tensor decompositionEvans, David and Ye, Nan (2023). Blockwise acceleration of alternating least squares for canonical tensor decomposition. Numerical Linear Algebra with Applications, 30 (6) e2516. doi: 10.1002/nla.2516 |
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2023 Journal Article Multi-pass Bayesian estimation: a robust Bayesian methodLei, Yeming, Zhou, Shijie, Filar, Jerzy and Ye, Nan (2023). Multi-pass Bayesian estimation: a robust Bayesian method. Computational Statistics, 39 (4), 2183-2216. doi: 10.1007/s00180-023-01390-0 |
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2023 Journal Article Model‐based offline reinforcement learning for sustainable fishery managementJu, Jun, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2023). Model‐based offline reinforcement learning for sustainable fishery management. Expert Systems, 42 (1) e13324. doi: 10.1111/exsy.13324 |
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2022 Conference Publication Adaptive Discretization Using Voronoi Trees for Continuous-Action POMDPsHoerger, Marcus, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2022). Adaptive Discretization Using Voronoi Trees for Continuous-Action POMDPs. Fifteenth Workshop on the Algorithmic Foundations of Robotics WAFR 2022, College Park, MD United States, 22-24 June 2022. Cham, Switzerland: Springer. doi: 10.1007/978-3-031-21090-7_11 |
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2022 Conference Publication Positive-unlabeled learning using random forests via recursive greedy risk minimizationWilton, Jonathan, Koay, Abigail M. Y., Ko, Ryan K. L., Miao Xu and Ye, Nan (2022). Positive-unlabeled learning using random forests via recursive greedy risk minimization. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, United States, 29 November - 1 December 2022. New Orleans, LA, United States: Neural information processing systems foundation. |
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2021 Conference Publication MOOR: Model-based offline reinforcement learning for sustainable fishery managementJu, Jun, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2021). MOOR: Model-based offline reinforcement learning for sustainable fishery management. 24th International Congress on Modelling and Simulation, Sydney, NSW, Australia, 5 - 10 December 2021. Sydney, NSW, Australia: International Congress on Modelling and Simulation. doi: 10.36334/modsim.2021.M2.ju |
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2021 Conference Publication Prior versus data: A new Bayesian method for fishery stock assessmentLei, Y., Zhou, S. and Ye, N. (2021). Prior versus data: A new Bayesian method for fishery stock assessment. 24th International Congress on Modelling and Simulation, Sydney, NSW, Australia, 5 - 10 December 2021. Sydney, NSW, Australia: International Congress on Modelling and Simulation. doi: 10.36334/modsim.2021.A1.lei |
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2020 Conference Publication Revisiting Maximum Entropy Inverse Reinforcement Learning: New Perspectives and AlgorithmsSnoswell, Aaron J., Singh, Surya P. N. and Ye, Nan (2020). Revisiting Maximum Entropy Inverse Reinforcement Learning: New Perspectives and Algorithms. 2020 IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, ACT Australia, 1-4 December 2020. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/SSCI47803.2020.9308391 |
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2020 Journal Article Reading both single and multiple digital video clocks using context-aware pixel periodicity and deep learningYu, Xinguo, Song, Wu, Lyu, Xiaopan, He, Bin and Ye, Nan (2020). Reading both single and multiple digital video clocks using context-aware pixel periodicity and deep learning. International Journal of Digital Crime and Forensics, 12 (2), 21-39. doi: 10.4018/IJDCF.2020040102 |
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2020 Conference Publication Discriminative particle filter reinforcement learning for complex partial observationsMa, Xiao, Karkus, Peter, Hsu, David, Lee, Wee Sun and Ye, Nan (2020). Discriminative particle filter reinforcement learning for complex partial observations. ICLR 2020: Eighth International Conference on Learning Representations, Virtual, 26 April - 1 May 2020. International Conference on Learning Representations, ICLR. |
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2020 Conference Publication Greedy convex ensembleNguyen, Thanh Tan, Ye, Nan and Bartlett, Peter (2020). Greedy convex ensemble. Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20), Online, 7-15 January 2021. Palo Alto, CA United States: A A A I Press. doi: 10.24963/ijcai.2020/429 |
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2020 Journal Article Nesterov acceleration of alternating least squares for canonical tensor decomposition: Momentum step size selection and restart mechanismsMitchell, Drew, Ye, Nan and De Sterck, Hans (2020). Nesterov acceleration of alternating least squares for canonical tensor decomposition: Momentum step size selection and restart mechanisms. Numerical Linear Algebra with Applications, 27 (4) e2297. doi: 10.1002/nla.2297 |
