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2024 Journal Article Non-uniform smoothness for gradient descentBerahas, Albert S., Roberts, Lindon and Roosta, Fred (2024). Non-uniform smoothness for gradient descent. Transactions on Machine Learning Research. |
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2024 Conference Publication Inexact Newton-type methods for optimisation with nonnegativity constraintsSmee, Oscar and Roosta, Fred (2024). Inexact Newton-type methods for optimisation with nonnegativity constraints. International Conference on Machine Learning, Vienna, Austria, 21-27 July 2024. Proceedings of Machine Learning Research. |
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2024 Conference Publication Manifold integrated gradients: Riemannian geometry for feature attributionZaher, Eslam, Trzaskowski, Maciej, Nguyen, Quan and Roosta, Fred (2024). Manifold integrated gradients: Riemannian geometry for feature attribution. International Conference on Machine Learning, Vienna, Austria, 21-27 July 2024. Proceedings of Machine Learning Research. |
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2023 Conference Publication Monotonicity and double descent in uncertainty estimation with gaussian processesHodgkinson, Liam, Van Der Heide, Chris, Roosta, Fred and Mahoney, Michael W. (2023). Monotonicity and double descent in uncertainty estimation with gaussian processes. International Conference on Machine Learning, Honolulu, HI United States, 23 - 29 July 2023. San Diego, CA United States: International Conference on Machine Learning. |
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2023 Journal Article Generalising uncertainty improves accuracy and safety of deep learning analytics applied to oncologyMacDonald, Samual, Foley, Helena, Yap, Melvyn, Johnston, Rebecca L., Steven, Kaiah, Koufariotis, Lambros T., Sharma, Sowmya, Wood, Scott, Addala, Venkateswar, Pearson, John V., Roosta, Fred, Waddell, Nicola, Kondrashova, Olga and Trzaskowski, Maciej (2023). Generalising uncertainty improves accuracy and safety of deep learning analytics applied to oncology. Scientific Reports, 13 (1) 7395, 1-14. doi: 10.1038/s41598-023-31126-5 |
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2023 Journal Article Inexact Newton-CG algorithms with complexity guaranteesYao, Zhewei, Xu, Peng, Roosta, Fred, Wright, Stephen J. and Mahoney, Michael W. (2023). Inexact Newton-CG algorithms with complexity guarantees. IMA Journal of Numerical Analysis, 43 (3), 1855-1897. doi: 10.1093/imanum/drac043 |
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2022 Journal Article MINRES: From negative curvature detection to monotonicity propertiesLiu, Yang and Roosta, Fred (2022). MINRES: From negative curvature detection to monotonicity properties. SIAM Journal on Optimization, 32 (4), 2636-2661. doi: 10.1137/21m143666x |
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2022 Journal Article Confirming the Lassonde Curve through life cycle analysis and its effect on share price: A case study of three ASX listed gold companiesRijsdijk, Timothy, Nehring, Micah, Kizil, Mehmet and Roosta, Fred (2022). Confirming the Lassonde Curve through life cycle analysis and its effect on share price: A case study of three ASX listed gold companies. Resources Policy, 77 102704, 1-12. doi: 10.1016/j.resourpol.2022.102704 |
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2022 Journal Article Newton-MR: inexact Newton Method with minimum residual sub-problem solverRoosta, Fred, Liu, Yang, Xu, Peng and Mahoney, Michael W. (2022). Newton-MR: inexact Newton Method with minimum residual sub-problem solver. EURO Journal on Computational Optimization, 10 100035, 1-44. doi: 10.1016/j.ejco.2022.100035 |
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2022 Conference Publication Crop type prediction utilising a long short-term memory with a self-attention for winter crops in AustraliaNguyen, Dung, Zhao, Yan, Zhang, Yifan, Huynh, Anh Ngoc-Lan, Roosta, Fred, Hammer, Graeme, Chapman, Scott and Potgieter, Andries (2022). Crop type prediction utilising a long short-term memory with a self-attention for winter crops in Australia. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17-22 July 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IGARSS46834.2022.9883737 |
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2022 Journal Article LSAR: efficient leverage score sampling algorithm for the analysis of big time series dataEshragh, Ali, Roosta, Fred, Nazari, Asef and Mahoney, Michael W. (2022). LSAR: efficient leverage score sampling algorithm for the analysis of big time series data. Journal of Machine Learning Research, 23, 1-36. |
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2021 Journal Article Implicit Langevin algorithms for sampling from log-concave densitiesHodgkinson, Liam, Salomone, Robert and Roosta, Fred (2021). Implicit Langevin algorithms for sampling from log-concave densities. Journal of Machine Learning Research, 22 136, 1-30. |
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2021 Conference Publication Shadow Manifold Hamiltonian Monte Carlovan der Heide, Chris, Hodgkinson, Liam, Roosta, Fred and Kroese, Dirk (2021). Shadow Manifold Hamiltonian Monte Carlo. International Conference on Artificial Intelligence and Statistics, Online, 27-30- July 2021. Tempe, AZ, United States: ML Research Press. |
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2021 Journal Article Evolution and application of digital technologies to predict crop type and crop phenology in agriculturePotgieter, A. B., Zhao, Yan, Zarco-Tejada, Pablo J, Chenu, Karine, Zhang, Yifan, Porker, Kenton, Biddulph, Ben, Dang, Yash P., Neale, Tim, Roosta, Fred and Chapman, Scott (2021). Evolution and application of digital technologies to predict crop type and crop phenology in agriculture. In Silico Plants, 3 (1) diab017, 1-23. doi: 10.1093/insilicoplants/diab017 |
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2021 Journal Article Inexact nonconvex Newton-type methodsYao, Zhewei, Xu, Peng, Roosta, Fred and Mahoney, Michael W. (2021). Inexact nonconvex Newton-type methods. INFORMS Journal on Optimization, 3 (2), 154-182. doi: 10.1287/ijoo.2019.0043 |
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2021 Journal Article Convergence of Newton-mr under inexact hessian informationLiu, Yang and Roosta, Fred (2021). Convergence of Newton-mr under inexact hessian information. SIAM Journal on Optimization, 31 (1), 59-90. doi: 10.1137/19M1302211 |
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2021 Conference Publication Avoiding kernel fixed points: Computing with ELU and GELU infinite networksTsuchida, Russell, Pearce, Tim, van der Heide, Chris, Roosta, Fred and Gallagher, Marcus (2021). Avoiding kernel fixed points: Computing with ELU and GELU infinite networks. 35th AAAI Conference on Artificial Intelligence, AAAI 2021, Online, 2 - 9 February 2021. Menlo Park, CA United States: Association for the Advancement of Artificial Intelligence. |
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2021 Conference Publication Non-PSD matrix sketching with applications to regression and optimizationFeng, Zhili, Roosta, Fred and Woodruff, David P. (2021). Non-PSD matrix sketching with applications to regression and optimization. Conference on Uncertainty in Artificial Intelligence, Online, 27-29 July 2021. San Diego, CA, United States: Association For Uncertainty in Artificial Intelligence (AUAI). |
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2021 Conference Publication Avoiding kernel fixed points: computing with ELU and GELU infinite networksTsuchida, Russell, Pearce, Tim, van der Heide, Chris, Roosta, Fred and Gallagher, Marcus (2021). Avoiding kernel fixed points: computing with ELU and GELU infinite networks. 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence, Electr Network, 2-9 February 2021. Washington, DC, United States: Association for the Advancement of Artificial Intelligence. |
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2021 Journal Article Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddingsLevin, Keith D., Roosta, Fred, Tang, Minh, Mahoney, Michael W. and Priebe, Carey E. (2021). Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings. Journal of Machine Learning Research, 22 194, 1-59. |
