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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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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 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 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 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. |
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2020 Journal Article Newton-type methods for non-convex optimization under inexact Hessian informationXu, Peng, Roosta, Fred and Mahoney, Michael W. (2020). Newton-type methods for non-convex optimization under inexact Hessian information. Mathematical Programming, 184 (1-2), 35-70. doi: 10.1007/s10107-019-01405-z |
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2018 Journal Article Sub-sampled Newton methodsRoosta-Khorasani, Farbod and Mahoney, Michael W. (2018). Sub-sampled Newton methods. Mathematical Programming, 174 (1-2), 293-326. doi: 10.1007/s10107-018-1346-5 |
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2017 Journal Article Variational perspective on local graph clusteringFountoulakis, Kimon, Roosta-Khorasani, Farbod, Shun, Julian, Cheng, Xiang and Mahoney, Michael W. (2017). Variational perspective on local graph clustering. Mathematical Programming, 174 (1-2), 553-573. doi: 10.1007/s10107-017-1214-8 |
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2016 Journal Article Algorithms that satisfy a stopping criterion, probablyAscher, Uri and Roosta-Khorasani, Farbod (2016). Algorithms that satisfy a stopping criterion, probably. Vietnam Journal of Mathematics, 44 (1), 49-69. doi: 10.1007/s10013-015-0167-6 |
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2015 Journal Article Schur properties of convolutions of gamma random variablesRoosta-Khorasani, Farbod and Szekely, Gábor J. (2015). Schur properties of convolutions of gamma random variables. Metrika, 78 (8), 997-1014. doi: 10.1007/s00184-015-0537-9 |
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2015 Journal Article Improved bounds on sample size for implicit matrix trace estimatorsRoosta-Khorasani, Farbod and Ascher, Uri (2015). Improved bounds on sample size for implicit matrix trace estimators. Foundations of Computational Mathematics, 15 (5), 1187-1212. doi: 10.1007/s10208-014-9220-1 |
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2015 Journal Article Assessing stochastic algorithms for large scale nonlinear least squares problems using extremal probabilities of linear combinations of gamma random variablesRoosta-Khorasani, Farbod, Székely, Gábor J. and Ascher, Uri M. (2015). Assessing stochastic algorithms for large scale nonlinear least squares problems using extremal probabilities of linear combinations of gamma random variables. SIAM/ASA Journal on Uncertainty Quantification, 3 (1), 61-90. doi: 10.1137/14096311X |
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2014 Journal Article Stochastic algorithms for inverse problems involving pdes and many measurementsRoosta-Khorasani, Farbod, Van Den Doel, Kees and Ascher, Uri (2014). Stochastic algorithms for inverse problems involving pdes and many measurements. SIAM Journal on Scientific Computing, 36 (5), S3-S22. doi: 10.1137/130922756 |
