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2024 |
Emmanuel Akeweje and Mimi Zhang |
Learning Mixtures of Gaussian Processes through Random Projection Proceedings of the 41st International Conference on Machine Learning (ICML) |
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2024 |
Joshua Tobin and Mimi Zhang |
A Theoretical Analysis of Density Peaks Clustering and the Component-wise Peak-Finding Algorithm IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(2), pp1109-1120 |
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2024 |
Emmanuel Akeweje and Mimi Zhang |
Learning Mixtures of Gaussian Processes through Random Projection 41st International Conference on Machine Learning |
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2024 |
Pangbo Ren, Charles Stuart, Mimi Zhang, Ryosuke Inomata, Kazuaki Nakamura, Isao Morita, Stephen Spence |
Investigation of the surrogate model in an ANN-Meanline Hybrid model for Radial Turbine Performance Prediction International Journal of Gas Turbine, Propulsion and Power Systems, 15(2), pp9-18. DOI: https://doi.org/10.38036/jgpp.15.2_9 |
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2024 |
Sukriti Dhang, Mimi Zhang and Soumyabrata Dev |
AdSegNet: A deep network to localize billboard in outdoor scenes Signal, Image and Video Processing, 18, pp7221-7235 |
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2024 |
Joshua Tobin, Michaela Black, James Ng, Debbie Rankin, Jonathan Wallace, Catherine Hughes, Leane Hoey, Adrian Moore, Jinling ... |
Co-Clustering Multi-View Data Using the Latent Block Model Computational Statistics & Data Analysis |
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2024 |
Guangchen Wang, Michael Monaghan and Mimi Zhang |
Parallelizing Adaptive Reliability Analysis through Penalizing the Learning Function IEEE Transactions on Reliability |
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2023 |
Bernard Fares and Mimi Zhang |
Incorporating Ignorance within Game Theory: An Imprecise Probability Approach International Journal of Approximate Reasoning, 154, pp133-148 |
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2023 |
Mimi Zhang and Andrew Parnell |
Review of Clustering Methods for Functional Data ACM Transactions on Knowledge Discovery from Data, 17(7), pp1-34 |
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2023 |
Joshua Tobin, Chin Pang Ho and Mimi Zhang |
Reinforced EM Algorithm for Clustering with Gaussian Mixture Models 2023 SIAM International Conference on Data Mining (SDM), pp118-126 |
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2022 |
Mimi Zhang |
Weighted Clustering Ensemble: A Review Pattern Recognition, 124, pp108428 |
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2022 |
Mimi Zhang, Matthew Revie and John Quigley |
Saddlepoint Approximation for the Generalized Inverse Gaussian Levy Process Journal of Computational and Applied Mathematics, 411, pp114275 |
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2022 |
Mimi Zhang and Bin Liu |
Discussion of signature-based models of preventive maintenance Applied Stochastic Models in Business and Industry, 39(1), pp54-56 |
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2022 |
Nuno Neto, Sinead O'Rourke, Mimi Zhang, Hannah Fitzgerald, Aisling Dunne and Michael Monaghan |
Non-Invasive classification of macrophage polarisation by 2P-FLIM and machine learning eLife, 11 |
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2021 |
Min Xie and Mimi Zhang |
Discussion of "Virtual age, is it real?" Applied Stochastic Models in Business and Industry, 37(1), pp30-31 |
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2021 |
Muhannad Ahmed Obeidi, Medad Monu, Cian Hughes, Declan Bourke, Merve Nur Dogu, Joshua Francis, Mimi Zhang, Inam Ul Ahad and D... |
Laser beam powder bed fusion of nitinol shape memory alloy (SMA) Journal of Materials Research and Technology, 14, pp2554-2570. DOI: https://doi.org/10.1016/j.jmrt.2021.07.126 |
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2021 |
Joshua Tobin and Mimi Zhang |
DCF: An Efficient and Robust Density-Based Clustering Method 2021 IEEE International Conference on Data Mining (ICDM), pp629-638 |
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2020 |
Mimi Zhang |
A Heuristic Policy for Maintaining Multiple Multi-State Systems Reliability Engineering and System Safety, 203, pp107081 |
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2019 |
Mimi Zhang |
Forward-Stagewise Clustering: An Algorithm for Convex Clustering Pattern Recognition Letters, 128, pp283-289 |
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2019 |
Mimi Zhang |
The Restless Bandits Problem with Partially Observable Markov Decision Processes Operations Research Letters |
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2019 |
Mimi Zhang |
Multivariate Modeling as Supervised Learning: the Pair Copula Construction Approach Computational Statistics and Data Analysis |
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2019 |
Mimi Zhang, Matthew Revie and John Quigley |
The Generalized Inverse Gaussian Levy Process Statistica Sinica |
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2018 |
Mimi Zhang and Tim Bedford |
Vine Copula Approximation: A Generic Method for Coping with Conditional Dependence Statistics and Computing, 28(1), pp219-237 |
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2017 |
Mimi Zhang and Min Xie |
An Ameliorated Improvement Factor Model for Imperfect Maintenance and Its Goodness of Fit Technometrics, 59 (2), pp237-246 |
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2017 |
Mimi Zhang and Matthew Revie |
Continuous-Observation Partially Observable Semi-Markov Decision Processes for Machine Maintenance IEEE Transactions on Reliability, 66 (1), pp202-218 |
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2016 |
Mimi Zhang and Matthew Revie |
Model selection with application to gamma process and inverse Gaussian process European Safety and Reliability Conference 2016 |
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2015 |
Mimi Zhang, Olivier Gaudoin and Min Xie |
Degradation-Based Maintenance Using Stochastic Filtering for Systems under Imperfect Maintenance European Journal of Operational Research, 245 (2), pp531-541 |
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2014 |
Mimi Zhang, Qingpei Hu, Min Xie and Dan Yu |
Lower Confidence Limit for Reliability Based on Grouped Data with a Quantile Filling Algorithm Computational Statistics & Data Analysis, 75, pp96-111 |
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2014 |
Mimi Zhang, Zhisheng Ye and Min Xie |
A Stochastic EM Algorithm for Progressively Censored Data Analysis Quality and Reliability Engineering International, 30 (5), pp711-722 |
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2014 |
Mimi Zhang, Zhisheng Ye and Min Xie |
A Condition-Based Maintenance Strategy for Heterogeneous Populations Computers & Industrial Engineering, 77, pp103-114 |
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2013 |
Mimi Zhang, Min Xie and Olivier Gaudoin |
A Bivariate Maintenance Policy for Multi-State Repairable Systems with Monotone Process IEEE Transactions on Reliability, 62 (4), pp876-886 |
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2013 |
Mimi Zhang and Min Xie |
Degradation modeling using stochastic filtering for systems under imperfect maintenance Prognostics and System Health Management Conference (PHM 2013), 33, pp7-12 |
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2013 |
Zhisheng Ye, Mimi Zhang and Xun Xiao |
An inspection-maintenance strategy for heterogeneous systems with measurable degradation 2013 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pp1432-1437 |
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2013 |
Mimi Zhang, Zhisheng Ye and Min Xie |
Optimal Burn-in Policy for Highly Reliable Products Using Inverse Gaussian Degradation Process 8th World Congress on Engineering Asset Management (WCEAM 2013), pp1003-1011 |