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Sam Davanloo Tajbakhsh

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2020 – today

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2024
[c1]
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  - conf/aistats/LiuT24
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Yin Liu, Sam Davanloo Tajbakhsh:
Fitting ARMA Time Series Models without Identification: A Proximal Approach. AISTATS 2024: 3835-3843
2023
[j5]
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Dewei Zhang, Sam Davanloo Tajbakhsh:
Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method for Submanifold Optimization. J. Optim. Theory Appl. 196(1): 324-361 (2023)
[j4]
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Yin Liu, Sam Davanloo Tajbakhsh:
Stochastic Composition Optimization of Functions Without Lipschitz Continuous Gradient. J. Optim. Theory Appl. 198(1): 239-289 (2023)
2022
[j3]
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  - journals/informs/ZhangLT22
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Dewei Zhang, Yin Liu, Sam Davanloo Tajbakhsh:
A First-Order Optimization Algorithm for Statistical Learning with Hierarchical Sparsity Structure. INFORMS J. Comput. 34(2): 1126-1140 (2022)
[i1]
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  - journals/corr/abs-2207-09350
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Dewei Zhang, Sam Davanloo Tajbakhsh:
Riemannian Stochastic Gradient Method for Nested Composition Optimization. CoRR abs/2207.09350 (2022)

2010 – 2019

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2015
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Sam Davanloo Tajbakhsh, Enrique del Castillo, James L. Rosenberger:
A Bayesian Approach to Sequential Optimization based on Computer Experiments. Qual. Reliab. Eng. Int. 31(6): 1001-1012 (2015)
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  - journals/technometrics/CastilloCT15
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Enrique del Castillo, Bianca Maria Colosimo, Sam Davanloo Tajbakhsh:
Geodesic Gaussian Processes for the Parametric Reconstruction of a Free-Form Surface. Technometrics 57(1): 87-99 (2015)

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