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Sam Davanloo Tajbakhsh
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Year
Phase II monitoring of nonlinear profiles
A Vaghefi, SD Tajbakhsh, R Noorossana
Communications in Statistics—Theory and Methods 38 (11), 1834-1851, 2009
1222009
An artificial neural network approach to multiple-response optimization
R Noorossana, S Davanloo Tajbakhsh, A Saghaei
The International Journal of Advanced Manufacturing Technology 40, 1227-1238, 2009
842009
Geodesic Gaussian processes for the parametric reconstruction of a free-form surface
E Del Castillo, BM Colosimo, SD Tajbakhsh
Technometrics 57 (1), 87-99, 2015
602015
A Bayesian approach to sequential optimization based on computer experiments
SD Tajbakhsh, E Del Castillo, JL Rosenberger
Quality and Reliability Engineering International 31 (6), 1001-1012, 2015
142015
On the theoretical guarantees for parameter estimation of gaussian random field models: A sparse precision matrix approach
SD Tajbakhsh, NS Aybat, E Del Castillo
Journal of Machine Learning Research 21 (217), 1-41, 2020
12*2020
Generalized sparse precision matrix selection for fitting multivariate gaussian random fields to large data sets
SD Tajbakhsh, NS Aybat, E Del Castillo
Statistica Sinica, 941-962, 2018
72018
Riemannian stochastic variance-reduced cubic regularized Newton method
D Zhang, SD Tajbakhsh
arXiv preprint arXiv:2010.03785, 2020
62020
Sparse precision matrix selection for fitting gaussian random field models to large data sets
S Davanloo Tajbakhsh, NS Aybat, E Del Castillo
arXiv preprint arXiv:1405.5576, 2015
52015
Fitting arma time series models without identification: A proximal approach
Y Liu, SD Tajbakhsh
arXiv preprint arXiv:2002.06777, 2020
42020
Riemannian stochastic variance-reduced cubic regularized Newton method for submanifold optimization
D Zhang, S Davanloo Tajbakhsh
Journal of Optimization Theory and Applications 196 (1), 324-361, 2023
32023
A first-order optimization algorithm for statistical learning with hierarchical sparsity structure
D Zhang, Y Liu, S Davanloo Tajbakhsh
INFORMS Journal on Computing 34 (2), 1126-1140, 2022
32022
Spatiotemporal wind forecasting by learning a hierarchically sparse inverse covariance matrix using wind directions
Y Liu, SD Tajbakhsh, AJ Conejo
International Journal of Forecasting 37 (2), 812-824, 2021
32021
Multi-scale biological and physical modelling of the tumour micro-environment
RF Kunz, BJ Gaskin, Q Li, S Davanloo-Tajbakhsh, C Dong
Drug Discovery Today: Disease Models 16, 7-15, 2015
32015
Important issues in multiple response optimization
SD Tajbakhsh, R Noorossana
4th International Management Conference 1, 2006
32006
Riemannian Stochastic Gradient Method for Nested Composition Optimization
D Zhang, SD Tajbakhsh
arXiv preprint arXiv:2207.09350, 2022
12022
Stochastic Composition Optimization of Functions Without Lipschitz Continuous Gradient
Y Liu, S Davanloo Tajbakhsh
Journal of Optimization Theory and Applications 198 (1), 239-289, 2023
2023
Adaptive Stochastic Optimization Algorithms for Problems with Biased Oracles
Y Liu, SD Tajbakhsh
arXiv preprint arXiv:2306.07810, 2023
2023
Supplementary Material: Geodesic Gaussian Processes for the Parametric Reconstruction of a Free-Form Surface
E Del Castillo, BM Colosimo, S Davanloo
Quality Engineering, 2015
2015
On convex optimization methods for fitting spatial statistical models to large data sets
SD Tajbakhsh
The Pennsylvania State University, 2015
2015
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Articles 1–19