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2024

Conference Publication

Fast controllable diffusion models for undersampled MRI reconstruction

Jiang, 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

Fast controllable diffusion models for undersampled MRI reconstruction

2024

Conference Publication

Robust loss functions for training decision trees with noisy labels

Wilton, 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

Robust loss functions for training decision trees with noisy labels

2024

Conference Publication

A surprisingly simple continuous-action POMDP solver: lazy cross-entropy search over policy trees

Hoerger, 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

A surprisingly simple continuous-action POMDP solver: lazy cross-entropy search over policy trees

2022

Conference Publication

Adaptive Discretization Using Voronoi Trees for Continuous-Action POMDPs

Hoerger, 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

Adaptive Discretization Using Voronoi Trees for Continuous-Action POMDPs

2022

Conference Publication

Positive-unlabeled learning using random forests via recursive greedy risk minimization

Wilton, 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.

Positive-unlabeled learning using random forests via recursive greedy risk minimization

2021

Conference Publication

Prior versus data: A new Bayesian method for fishery stock assessment

Lei, 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

Prior versus data: A new Bayesian method for fishery stock assessment

2021

Conference Publication

MOOR: Model-based offline reinforcement learning for sustainable fishery management

Ju, 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

MOOR: Model-based offline reinforcement learning for sustainable fishery management

2020

Conference Publication

Revisiting Maximum Entropy Inverse Reinforcement Learning: New Perspectives and Algorithms

Snoswell, 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

Revisiting Maximum Entropy Inverse Reinforcement Learning: New Perspectives and Algorithms

2020

Conference Publication

Greedy convex ensemble

Nguyen, 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

Greedy convex ensemble

2020

Conference Publication

Discriminative particle filter reinforcement learning for complex partial observations

Ma, 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.

Discriminative particle filter reinforcement learning for complex partial observations

2019

Conference Publication

POMDPs for sustainable fishery management

Filar, Jerzy A., Qiao, Zhihao and Ye, Nan (2019). POMDPs for sustainable fishery management. International Congress on Modelling and Simulation, Canberra, Australia, 1-6 December 2019. Modelling and Simulation Society of Australia and New Zealand. doi: 10.36334/modsim.2019.g2.filar

POMDPs for sustainable fishery management

2019

Conference Publication

Maximum entropy approaches for inverse reinforcement learning

Snoswell, A. J., Singh, S. P. N. and Ye, N. (2019). Maximum entropy approaches for inverse reinforcement learning. INFORMS-APS, Brisbane, Australia, 3-5 July 2019.

Maximum entropy approaches for inverse reinforcement learning

2017

Conference Publication

Modelling imperfect presence data obtained by citizen science

Mengersen, Kerrie, Peterson, Erin E., Clifford, Samuel, Ye, Nan, Kim, June, Bednarz, Tomasz, Brown, Ross, James, Allan, Vercelloni, Julie, Pearse, Alan R., Davis, Jacqueline and Hunter, Vanessa (2017). Modelling imperfect presence data obtained by citizen science. 26th Annual Conference of the International-Environmetrics-Society (TIES), Riccarton, Scotland, 18-22 July 2016. Oxford, United Kingdom: John Wiley & Sons. doi: 10.1002/env.2446

Modelling imperfect presence data obtained by citizen science

2017

Conference Publication

Tensor belief propagation

Wrigley, Andrew, Lee, Wee Sun and Ye, Nan (2017). Tensor belief propagation. 34th International Conference on Machine Learning, Sydney, NSW, Australia, 6-11 August 2017. San Diego, CA, United States: JMLR.org.

Tensor belief propagation

2016

Conference Publication

Robustness of Bayesian pool-based active learning against prior misspecification

Cuong, Nguyen Viet, Ye, Nan and Lee, Wee Sun (2016). Robustness of Bayesian pool-based active learning against prior misspecification. Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, AZ, United States, 12-17 February 2016. Palo Alto, CA, United States: AAAI Press.

Robustness of Bayesian pool-based active learning against prior misspecification

2015

Conference Publication

Intention-aware online POMDP planning for autonomous driving in a crowd

Bai, Haoyu, Cai, Shaojun, Ye, Nan, Hsu, David and Lee, Wee Sun (2015). Intention-aware online POMDP planning for autonomous driving in a crowd. 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA United States, 26-30 May 2015. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICRA.2015.7139219

Intention-aware online POMDP planning for autonomous driving in a crowd

2014

Conference Publication

Near-optimal adaptive pool-based active learning with general loss

Nguyen Viet Cuong, Lee, Wee Sun and Ye, Nan (2014). Near-optimal adaptive pool-based active learning with general loss. 30th Conference on Uncertainty in Artificial Intelligence (UAI), Quebec City, Canada, 23-27 July 2014. Arlington, VA, United States: AUAI Press.

Near-optimal adaptive pool-based active learning with general loss

2014

Conference Publication

Goal detection for broadcast basketball video using superimposed texts: A transition pattern approach

Ding, Wan, Yu, Xinguo and Ye, Nan (2014). Goal detection for broadcast basketball video using superimposed texts: A transition pattern approach. ICIMCS '14: International Conference on Internet Multimedia Computing and Service, Xiamen, China, 10-12 July 2014. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2632856.2632859

Goal detection for broadcast basketball video using superimposed texts: A transition pattern approach

2013

Conference Publication

Active learning for probabilistic hypotheses using the maximum Gibbs error criterion

Nguyen, Viet Cuong, Lee, Wee Sun, Ye, Nan, Chai, Kian Ming A. and Chieu, Hai Leong (2013). Active learning for probabilistic hypotheses using the maximum Gibbs error criterion. NIPS'13: 26th International Conference on Neural Information Processing Systems, Lake Tahoe, NV, United States, 5-10 December 2013. Red Hook, NY, United States: Curran Associates. doi: 10.5555/2999611.2999774

Active learning for probabilistic hypotheses using the maximum Gibbs error criterion

2013

Conference Publication

DESPOT: Online POMDP planning with regularization

Somani, Adhiraj, Ye, Nan, Hsu, David and Lee, Wee Sun (2013). DESPOT: Online POMDP planning with regularization. Advances in Neural Information Processing Systems 26 (NIPS 2013), Lake Tahoe, NV, United States, 5-10 December 2013. Neural information processing systems foundation.

DESPOT: Online POMDP planning with regularization