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ORCIDRaghu Pasupathy
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2020 – today
- 2024
[j16]Ziwei Su
, Raghu Pasupathy, Yingchieh Yeh, Peter W. Glynn:
Overlapping Batch Confidence Intervals on Statistical Functionals Constructed from Time Series: Application to Quantiles, Optimization, and Estimation. ACM Trans. Model. Comput. Simul. 34(2): 10:1-10:43 (2024)- [i4]Yunsoo Ha, Sara Shashaani, Raghu Pasupathy:
Complexity of Zeroth- and First-order Stochastic Trust-Region Algorithms. CoRR abs/2405.20116 (2024) - [i3]Mudit Gaur, Amrit Singh Bedi, Raghu Pasupathy, Vaneet Aggarwal:
On The Global Convergence Of Online RLHF With Neural Parametrization. CoRR abs/2410.15610 (2024) - 2023
- [c34]Raghu Pasupathy:
Bootstrapping And Batching For Output Analysis. WSC 2023: 61-75 - [i2]Ziwei Su, Raghu Pasupathy, Yingchieh Yeh, Peter W. Glynn:
Overlapping Batch Confidence Intervals on Statistical Functionals Constructed from Time Series: Application to Quantiles, Optimization, and Estimation. CoRR abs/2307.08609 (2023) - 2022
- [j15]Prasanna K. Ragavan, Susan R. Hunter, Raghu Pasupathy, Michael R. Taaffe:
Adaptive Sampling line search for local stochastic optimization with integer variables. Math. Program. 196(1): 775-804 (2022) - [c33]Raghu Pasupathy, Dashi I. Singham, Yingchieh Yeh:
Overlapping Batch Confidence Regions on the Steady-State Quantile Vector. WSC 2022: 25-36 - [c32]Zihe Zhou, Harsha Honnappa, Raghu Pasupathy:
Sample Average Approximation Over Function Spaces: Statistical Consistency and Rate of Convergence. WSC 2022: 61-72 - [c31]Susan R. Hunter, Raghu Pasupathy:
Central Limit Theorems for Constructing Confidence Regions in Strictly Convex Multi-Objective Simulation Optimization. WSC 2022: 3015-3026 - 2021
- [j14]Raghu Pasupathy, Yongjia Song:
Adaptive Sequential Sample Average Approximation for Solving Two-Stage Stochastic Linear Programs. SIAM J. Optim. 31(1): 1017-1048 (2021) - 2020
- [j13]Eric A. Applegate, Guy Feldman, Susan R. Hunter, Raghu Pasupathy:
Multi-objective ranking and selection: Optimal sampling laws and tractable approximations via SCORE. J. Simulation 14(1): 21-40 (2020) - [c30]Raghu Pasupathy, Yingchieh Yeh:
Risk-Efficient Sequential Simulation Estimators. WSC 2020: 2879-2886 - [i1]Raghu Pasupathy, Yongjia Song:
Adaptive Sequential SAA for Solving Two-stage Stochastic Linear Programs. CoRR abs/2012.03761 (2020)
2010 – 2019
- 2019
- [c29]David J. Eckman, Shane G. Henderson, Raghu Pasupathy:
Redesigning a Testbed of Simulation-Optimization Problems and Solvers for Experimental Comparisons. WSC 2019: 3457-3467 - [c28]Raghu Pasupathy:
The Number of Random Restarts Required to Identify all Solutions to a Nonlinear System: Applications to Global Stochastic Optimization. WSC 2019: 3540-3550 - [c27]Daniel Vasquez, Raghu Pasupathy, Sara Shashaani:
Astro for Derivative-Based Stochastic Optimization: Algorithm Description & Numerical Experiments. WSC 2019: 3563-3574 - 2018
- [j12]Raghu Pasupathy, Peter W. Glynn, Soumyadip Ghosh, Fatemeh Sadat Hashemi:
On Sampling Rates in Simulation-Based Recursions. SIAM J. Optim. 28(1): 45-73 (2018) - [j11]Sara Shashaani, Fatemeh Sadat Hashemi, Raghu Pasupathy:
ASTRO-DF: A Class of Adaptive Sampling Trust-Region Algorithms for Derivative-Free Stochastic Optimization. SIAM J. Optim. 28(4): 3145-3176 (2018) - [c26]David Newton, Raghu Pasupathy, Farzad Yousefian:
Recent Trends in stochastic Gradient Descent for Machine Learning and Big Data. WSC 2018: 366-380 - [c25]Prateek Jaiswal, Harsha Honnappa, Raghu Pasupathy:
Optimal Allocations for sample Average Approximation. WSC 2018: 1874-1885 - 2017
- [c24]Eric A. Applegate, Susan R. Hunter, Guy Feldman, Raghu Pasupathy:
Phantom pareto systems for multi-objective ranking and selection. WSC 2017: 4576-4577 - 2016
- [c23]Sara Shashaani, Susan R. Hunter, Raghu Pasupathy:
ASTRO-DF: Adaptive sampling trust-region optimization algorithms, heuristics, and numerical experience. WSC 2016: 554-565 - 2015
- [j10]Pengfei Li, Montasir Abbas, Raghu Pasupathy:
A Stochastic Dilemma Zone Protection Algorithm Based on the Vehicles' Trajectories. J. Intell. Transp. Syst. 19(2): 181-191 (2015) - [c22]Raghu Pasupathy, Kalyani Nagaraj:
Modeling dependence in simulation input: the case for copulas. WSC 2015: 1850-1864 - [c21]Guy Feldman, Susan R. Hunter, Raghu Pasupathy:
Multi-objective simulation optimization on finite sets: optimal allocation via scalarization. WSC 2015: 3106-3107 - [c20]Guy Feldman, Susan R. Hunter, Raghu Pasupathy:
Multi-objective simulation optimization on finite sets: optimal allocation via scalarization. WSC 2015: 3610-3621 - 2014
- [j9]Raghu Pasupathy, Susan R. Hunter, Nugroho Artadi Pujowidianto, Loo Hay Lee, Chun-Hung Chen:
Stochastically Constrained Ranking and Selection via SCORE. ACM Trans. Model. Comput. Simul. 25(1): 1:1-1:26 (2014) - [c19]Fatemeh Sadat Hashemi, Soumyadip Ghosh, Raghu Pasupathy:
On adaptive sampling rules for stochastic recursions. WSC 2014: 3959-3970 - 2013
- [j8]Susan R. Hunter, Raghu Pasupathy:
Optimal Sampling Laws for Stochastically Constrained Simulation Optimization on Finite Sets. INFORMS J. Comput. 25(3): 527-542 (2013) - [j7]Honggang Wang, Raghu Pasupathy, Bruce W. Schmeiser:
Integer-Ordered Simulation Optimization using R-SPLINE: Retrospective Search with Piecewise-Linear Interpolation and Neighborhood Enumeration. ACM Trans. Model. Comput. Simul. 23(3): 17:1-17:24 (2013) - [c18]Soumyadip Ghosh, Raghu Pasupathy:
Low-storage online estimators for quantiles and densities. WSC 2013: 778-789 - [c17]Kalyani Nagaraj, Raghu Pasupathy:
R-SPLINE for local integer-ordered simulation optimization problems with stochastic constraints. WSC 2013: 846-855 - 2012
- [j6]Soumyadip Ghosh, Raghu Pasupathy:
C-NORTA: A Rejection Procedure for Sampling from the Tail of Bivariate NORTA Distributions. INFORMS J. Comput. 24(2): 295-310 (2012) - [c16]Nugroho Artadi Pujowidianto, Susan R. Hunter, Raghu Pasupathy, Loo Hay Lee, Chun-Hung Chen:
Closed-form sampling laws for stochastically constrained simulation optimization on large finite sets. WSC 2012: 14:1-14:10 - [c15]Fatemeh Sadat Hashemi, Raghu Pasupathy:
Averaging and derivative estimation within stochastic approximation algorithms. WSC 2012: 20:1-20:9 - 2011
- [j5]Raghu Pasupathy, Sujin Kim:
The stochastic root-finding problem: Overview, solutions, and open questions. ACM Trans. Model. Comput. Simul. 21(3): 19:1-19:23 (2011) - [c14]Raghu Pasupathy:
An introspective on the retrospective-approximation paradigm. WSC 2011: 412-421 - [c13]Raghu Pasupathy, Shane G. Henderson:
SimOpt: a library of simulation optimization problems. WSC 2011: 4080-4090 - [c12]Soumyadip Ghosh, Raghu Pasupathy:
On interior-point based retrospective approximation methods for solving two-stage stochastic linear programs. WSC 2011: 4163-4171 - [c11]Susan R. Hunter, Chun-Hung Chen, Raghu Pasupathy, Nugroho Artadi Pujowidianto, Loo Hay Lee, Chee Meng Yap:
Optimal sampling laws for constrained simulation optimization on finite sets: the bivariate normal case. WSC 2011: 4294-4302 - 2010
- [j4]Kaeyoung Shin, Raghu Pasupathy:
An Algorithm for Fast Generation of Bivariate Poisson Random Vectors. INFORMS J. Comput. 22(1): 81-92 (2010) - [j3]Raghu Pasupathy:
On Choosing Parameters in Retrospective-Approximation Algorithms for Stochastic Root Finding and Simulation Optimization. Oper. Res. 58(4-Part-1): 889-901 (2010) - [c10]Raghu Pasupathy, Bruce W. Schmeiser:
The initial transient in steady-state point estimation: Contexts, a bibliography, the mse criterion, and the MSER statistic. WSC 2010: 184-197 - [c9]Susan R. Hunter, Raghu Pasupathy:
Large-deviation sampling laws for constrained simulation optimization on finite sets. WSC 2010: 995-1002 - [c8]Raghu Pasupathy, Bruce W. Schmeiser:
Root finding via DARTS - Dynamic Adaptive Random Target Shooting. WSC 2010: 1255-1262 - [c7]Raghu Pasupathy, Roberto Szechtman, Enver Yücesan:
Selecting small quantiles. WSC 2010: 2762-2770
2000 – 2009
- 2009
- [j2]Raghu Pasupathy, Bruce W. Schmeiser:
Retrospective-approximation algorithms for the multidimensional stochastic root-finding problem. ACM Trans. Model. Comput. Simul. 19(2): 5:1-5:36 (2009) - 2007
- [j1]Raghu Pasupathy, Samuel Labi, Kumares C. Sinha:
Optimal Reconstruction Periods for Stochastically Deteriorating Infrastructures. Comput. Aided Civ. Infrastructure Eng. 22(6): 389-399 (2007) - [c6]Kaeyoung Shin, Raghu Pasupathy:
A method for fast generation of bivariate Poisson random vectors. WSC 2007: 472-479 - 2006
- [c5]Raghu Pasupathy:
On choosing parameters in retrospective-approximation algorithms for simulation-optimization. WSC 2006: 208-215 - [c4]Raghu Pasupathy, Shane G. Henderson:
A testbed of simulation-optimization problems. WSC 2006: 255-263 - 2004
- [c3]Raghu Pasupathy, Bruce W. Schmeiser:
Retrospective Approximation Algorithms for the Multidimensional Stochastic Root-Finding Problem. WSC 2004: 520-528 - 2003
- [c2]Jamie R. Wieland, Raghu Pasupathy, Bruce W. Schmeiser:
Queueing network simulation analysis: queueing-network stability: simulation-based checking. WSC 2003: 520-527 - [c1]Raghu Pasupathy, Bruce W. Schmeiser:
Issues on simulation and optimization II: some issues in multivariate stochastic root finding. WSC 2003: 574-577
Coauthor Index
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