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  2020 (2)
An Adaptive Sequential Sample Average Approximation Framework for Solving Two-stage Stochastic Linear Programs. Pasupathy, R.; and Song, Y. SIAM Journal on Optimization. 2020. To appear.
An Adaptive Sequential Sample Average Approximation Framework for Solving Two-stage Stochastic Linear Programs [link]Paper   link   bibtex  
Adaptive Sampling Line Search for Stochastic Optimization with Integer Variables. Raghavan, P. K.; Hunter, S. R.; Pasupathy, R.; and Taaffe, M. R. Math. Programming. 2020.
Adaptive Sampling Line Search for Stochastic Optimization with Integer Variables [link]Paper   link   bibtex  
  2019 (5)
Multi-objective ranking and selection: optimal sampling laws and tractable approximations via SCORE. Applegate, E. A.; Feldman, G.; Hunter, S. R.; and Pasupathy, R. Journal of Simulation, 14(1): 21–40. 2019.
Multi-objective ranking and selection: optimal sampling laws and tractable approximations via SCORE [link]Paper   link   bibtex  
Open Problem–Adaptive Constant-Step Stochastic Approximation. Pasupathy, R.; Honnappa, H.; and Hunter, S. R. Stochastic Systems. 2019.
doi   link   bibtex   abstract  
The Ties that Bind. Leemis, L.; and Pasupathy, R. Significance, 16(4): 8-9. 2019.
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The Number of Random Restarts Required to Identify All Solutions to a Nonlinear System: Applications to Global Stochastic Optimization. Pasupathy, R. In Mustafee, N.; Bae, K.; Lazarova-Molnar, S.; Rabe, M.; Szabo, C.; Haas, P.; and Son, Y., editor(s), Proceedings of the 2019 Winter Simulation Conference, Piscataway, NJ, 2019. Institute of Electrical and Electronics Engineers, Inc.
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ASTRO for Derivative-based Stochastic Optimization: Algorithm Description & Numerical Experiments. Vasquez, D.; Shashaani, S.; and Pasupathy, R. In Mustafee, N.; Bae, K.; Lazarova-Molnar, S.; Rabe, M.; Szabo, C.; Haas, P.; and Son, Y., editor(s), Proceedings of the 2019 Winter Simulation Conference, Piscataway, NJ, 2019. Institute of Electrical and Electronics Engineers, Inc.
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  2018 (6)
Optimal placement of a small order in a diffusive limit order book. Figueroa-López, J. E.; Lee, H.; and Pasupathy, R. High Frequency, 1(2): 87–116. 2018.
Optimal placement of a small order in a diffusive limit order book [link] link   Optimal placement of a small order in a diffusive limit order book [pdf] paper   doi   link   bibtex  
ASTRO-DF: A Class of Adaptive Sampling Trust-Region Algorithms for Derivative-Free Simulation Optimization. Shashaani, S.; Hashemi, F. S.; and Pasupathy, R. SIAM Journal on Optimization,2753–3430. 2018.
ASTRO-DF: A Class of Adaptive Sampling Trust-Region Algorithms for Derivative-Free Simulation Optimization. [link] link   ASTRO-DF: A Class of Adaptive Sampling Trust-Region Algorithms for Derivative-Free Simulation Optimization. [pdf] paper   link   bibtex  
On sampling rates in simulation-based recursions. Pasupathy, R.; Glynn, P. W.; Ghosh, S.; and Hashemi, F. SIAM Journal on Optimization, 28(1): 45–73. 2018.
On sampling rates in simulation-based recursions. [link] link   On sampling rates in simulation-based recursions. [pdf] paper   link   bibtex  
Stochastic Gradient Descent: Modern Trends. Newton, D.; Yousefian, F.; and Pasupathy, R. In Gel, E.; and Lewis, D., editor(s), TutORials in Operations Research, 7. INFORMS, 2018.
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Optimal Allocations for Sample Average Approximation. Jaiswal, P.; Honnappa, H.; and Pasupathy, R. In Rabe, M.; Juan, A. A.; Mustafee, N.; Skoogh, A.; Jain, S.; and B. Johansson, e., editor(s), Proceedings of the 2018 Winter Simulation Conference, Piscataway, NJ, 2018. Institute of Electrical and Electronics Engineers, Inc.
Optimal Allocations for Sample Average Approximation [link]Paper   link   bibtex  
Recent Trends in Stochastic Gradient Descent for Machine Learning and Big Data. Newton, D.; Yousefian, F.; and Pasupathy, R. In Rabe, M.; Juan, A. A.; Mustafee, N.; Skoogh, A.; Jain, S.; and B. Johansson, e., editor(s), Proceedings of the 2018 Winter Simulation Conference, Piscataway, NJ, 2018. Institute of Electrical and Electronics Engineers, Inc.
Recent Trends in Stochastic Gradient Descent for Machine Learning and Big Data [link]Paper   link   bibtex  
  2017 (3)
The Adaptive Sampling Gradient Method: Optimizing Smooth Functions with an Inexact Oracle. Hashemi, F. S.; Pasupathy, R.; and Taaffe, M. R. . 2017.
The Adaptive Sampling Gradient Method: Optimizing Smooth Functions with an Inexact Oracle [link] link   The Adaptive Sampling Gradient Method: Optimizing Smooth Functions with an Inexact Oracle [pdf] paper   link   bibtex  
Stochastically Constrained Simulation Optimization On Integer-Ordered Spaces: The cgR-SPLINE Algorithm. Nagaraj, K.; and Pasupathy, R. Operations Research. 2017.
Stochastically Constrained Simulation Optimization On Integer-Ordered Spaces: The cgR-SPLINE Algorithm [link] link   Stochastically Constrained Simulation Optimization On Integer-Ordered Spaces: The cgR-SPLINE Algorithm [pdf] paper   link   bibtex  
Moment-Ratio Diagrams for Univariate Distributions. Vargo, E.; Pasupathy, R.; and Leemis, L. M. In Glen, A. G.; and Leemis, L. M., editor(s), Computational Probability and Applications. 2017.
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  2016 (1)
ASTRO-DF: Adaptive Sampling Trust-Region Optimization Algorithms, Heuristics, and Numerical Experience. Shashaani, S.; Hunter, S. R.; and Pasupathy, R. In Roeder, T. M. K.; Frazier, P. I.; Szechtman, R.; and Zhou, E., editor(s), Proceedings of the 2016 Winter Simulation Conference, Piscataway, NJ, 2016. Institute of Electrical and Electronics Engineers, Inc.
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  2015 (2)
Multi-objective simulation optimization on finite sets: optimal allocation via scalarization. Feldman, G.; Hunter, S. R.; and Pasupathy, R. In Yilmaz, L.; Chan, W. K. V.; Moon, I.; Roeder, T. M. K.; Macal, C.; and Rossetti, M. D., editor(s), Proceedings of the 2015 Winter Simulation Conference, Piscataway, NJ, 2015. Institute of Electrical and Electronics Engineers, Inc.
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Modeling Dependence in Simulation Input: The Case for Copulas. Nagaraj, K.; and Pasupathy, R. In Yilmaz, L.; Chan, W. K. V.; Moon, I.; Roeder, T. M. K.; Macal, C.; and Rossetti, M. D., editor(s), Proceedings of the 2015 Winter Simulation Conference, Piscataway, NJ, 2015. Institute of Electrical and Electronics Engineers, Inc.
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  2014 (5)
A Stochastic Dilemma Zone Protection Algorithm Based On Vehicle Trajectories. Li, P.; Abbas, M.; and Pasupathy, R. Journal of Intelligent Transportation Systems. 2014.
doi   link   bibtex   abstract  
Stochastically constrained ranking and selection via SCORE. Pasupathy, R.; Hunter, S. R.; Pujowidianto, N. A.; Lee, L. H.; and Chen, C. ACM Transactions on Modeling and Computer Simulation, 25(1): 1–26. 2014.
Stochastically constrained ranking and selection via SCORE [link] link   Stochastically constrained ranking and selection via SCORE [pdf] paper   doi   link   bibtex   abstract  
Control-variate estimation using estimated control means. Pasupathy, R.; Taaffe, M.; Schmeiser, B. W.; and Wang, W. IIE Transactions, 44(5): 381–385. 2014.
Control-variate estimation using estimated control means [pdf]Paper   doi   link   bibtex   abstract  
A Guide to SAA. Kim, S.; Pasupathy, R.; and Henderson, S. G. In Fu, M., editor(s), Encyclopedia of Operations Research and Management Science, of Hillier and Lieberman OR Series. Elsevier, 2014.
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On adaptive sampling rules for stochastic recursions. Hashemi, F.; Ghosh, S.; and Pasupathy, R. In Tolk, A.; Diallo, S. Y.; Ryzhov, I. O.; Yilmaz, L.; Buckley, S.; and Miller, J. A., editor(s), Proceedings of the 2014 Winter Simulation Conference, Piscataway, NJ, 2014. Institute of Electrical and Electronics Engineers, Inc.
On adaptive sampling rules for stochastic recursions [link]Paper   link   bibtex   abstract  
  2013 (5)
Integer-Ordered Simulation Optimization using R-SPLINE: Retrospective Search using Piecewise-Linear Interpolation and Neighborhood Enumeration. Wang, H.; Pasupathy, R.; and Schmeiser, B. W. ACM TOMACS, 23(3). 2013.
Integer-Ordered Simulation Optimization using R-SPLINE: Retrospective Search using Piecewise-Linear Interpolation and Neighborhood Enumeration [pdf]Paper   doi   link   bibtex   abstract  
Optimal sampling laws for stochastically constrained simulation optimization on finite sets. Hunter, S. R.; and Pasupathy, R. INFORMS Journal on Computing, 25(3): 527–542. 2013.
Optimal sampling laws for stochastically constrained simulation optimization on finite sets [link] link   Optimal sampling laws for stochastically constrained simulation optimization on finite sets [pdf] paper   doi   link   bibtex   abstract  
Simulation Optimization: A concise overview and implementation guide. Pasupathy, R.; and Ghosh, S. In Topaloglu, H., editor(s), TutORials in Operations Research, 7, pages 122–150. INFORMS, 2013.
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R-SPLINE for local integer-ordered simulation optimization problems with stochastic constraints. Nagaraj, K.; and Pasupathy, R. In Pasupathy, R.; Kim, S.; Tolk, A.; Hill, R.; and Kuhl, M. E., editor(s), Proceedings of the 2013 Winter Simulation Conference, pages 846–855, Piscataway, NJ, 2013. Institute of Electrical and Electronics Engineers, Inc.
R-SPLINE for local integer-ordered simulation optimization problems with stochastic constraints [pdf]Paper   link   bibtex   abstract  
Online quantile and density estimators. Ghosh, S.; and Pasupathy, R. In Pasupathy, R.; Kim, S.; Tolk, A.; Hill, R.; and Kuhl, M. E., editor(s), Proceedings of the 2013 Winter Simulation Conference, pages 778–789, Piscataway, NJ, 2013. Institute of Electrical and Electronics Engineers, Inc.
Online quantile and density estimators [pdf]Paper   link   bibtex   abstract  
  2012 (4)
A note on the number of random restarts required to approximate all solutions of a stochastic nonlinear system. Le, K.; and Pasupathy, R. Operations Research. 2012.
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C-NORTA: A rejection procedure for sampling from the tail of bivariate NORTA distributions. Ghosh, S.; and Pasupathy, R. INFORMS Journal on Computing, 24(2): 295–310. 2012.
C-NORTA: A rejection procedure for sampling from the tail of bivariate NORTA distributions [pdf]Paper   doi   link   bibtex   abstract  
Closed-Form Sampling Laws For Stochastically Constrained Simulation Optimization On Large Finite Sets. Pujowidianto, N. A.; Hunter, S. R.; Pasupathy, R.; Lee, L. H.; and Chen, C. In Laroque, C.; Himmelspach, J.; Pasupathy, R.; Rose, O.; and Uhrmacher, A. M., editor(s), Proceedings of the 2012 Winter Simulation Conference, pages 168–177, Piscataway, NJ, 2012. Institute of Electrical and Electronics Engineers, Inc.
Closed-Form Sampling Laws For Stochastically Constrained Simulation Optimization On Large Finite Sets [pdf]Paper   link   bibtex   abstract  
Averaging and Derivative Estimation Within Stochastic Approximation Algorithms. Hashemi, F.; and Pasupathy, R. In Laroque, C.; Himmelspach, J.; Pasupathy, R.; Rose, O.; and Uhrmacher, A., editor(s), Proceedings of the 2012 Winter Simulation Conference, pages 232–240, Piscataway, NJ, 2012. Institute of Electrical and Electronics Engineers, Inc.
Averaging and Derivative Estimation Within Stochastic Approximation Algorithms [pdf]Paper   link   bibtex   abstract  
  2011 (7)
The stochastic root-finding problem: overview, solutions, and open questions. Pasupathy, R.; and Kim, S. ACM TOMACS, 21(3): 23. 2011.
The stochastic root-finding problem: overview, solutions, and open questions [pdf]Paper   doi   link   bibtex   abstract  
Generating homogenous Poisson processes. Pasupathy, R. In Wiley Encyclopedia of Operations Research and Management Science. Wiley, 2011.
Generating homogenous Poisson processes [pdf]Paper   link   bibtex  
Generating nonhomogenous Poisson processes. Pasupathy, R. In Wiley Encyclopedia of Operations Research and Management Science. Wiley, 2011.
Generating nonhomogenous Poisson processes [pdf]Paper   link   bibtex  
On Interior-Point Based Retrospective Approximation Methods for Solving Two-Stage Stochastic Linear Programs. Ghosh, S.; and Pasupathy, R. In Jain, S.; Creasey, R. R.; Himmelspach, J.; White, K. P.; and Fu, M., editor(s), Proceedings of the 2011 Winter Simulation Conference, pages 4163–4171, Piscataway, NJ, 2011. Institute of Electrical and Electronics Engineers, Inc.
On Interior-Point Based Retrospective Approximation Methods for Solving Two-Stage Stochastic Linear Programs [pdf]Paper   link   bibtex   abstract  
Optimal sampling laws for constrained simulation optimization on finite sets: the bivariate normal case. Hunter, S. R.; Pujowidianto, N. A.; Chen, C.; Lee, L. H.; Pasupathy, R.; and Yap, C. M. In Jain, S.; Creasey, R. R.; Himmelspach, J.; White, K. P.; and Fu, M., editor(s), Proceedings of the 2011 Winter Simulation Conference, pages 4294–4302, Piscataway, NJ, 2011. Institute of Electrical and Electronics Engineers, Inc.
Optimal sampling laws for constrained simulation optimization on finite sets: the bivariate normal case [pdf]Paper   link   bibtex   abstract  
SimOpt: A Library of Simulation Optimization Problems. Pasupathy, R.; and Henderson, S. G. In Jain, S.; Creasey, R. R.; Himmelspach, J.; White, K. P.; and Fu, M., editor(s), Proceedings of the 2011 Winter Simulation Conference, pages 4080–4090, Piscataway, NJ, 2011. Institute of Electrical and Electronics Engineers, Inc.
SimOpt: A Library of Simulation Optimization Problems [pdf]Paper   link   bibtex   abstract  
An Introspective on the Retrospective-approximation Paradigm. Pasupathy, R. In Jain, S.; Creasey, R. R.; Himmelspach, J.; White, K. P.; and Fu, M., editor(s), Proceedings of the 2011 Winter Simulation Conference, pages 412–421, Piscataway, NJ, 2011. Institute of Electrical and Electronics Engineers, Inc.
An Introspective on the Retrospective-approximation Paradigm [pdf]Paper   link   bibtex   abstract  
  2010 (8)
Moment-ratio diagrams for univariate distributions. Vargo, E.; Pasupathy, R.; and Leemis, L. Journal of Quality Technology, 42(3): 276–286. 2010.
Moment-ratio diagrams for univariate distributions [pdf]Paper   link   bibtex   abstract  
Simulation-based optimization of maximum green setting under retrospective approximation framework. Li, P.; Abbas, M.; Pasupathy, R.; and Head, L. Transportation Research, 2192: 1–10. 2010.
doi   link   bibtex   abstract  
A method for fast generation of Poisson random vectors. Shin, K.; and Pasupathy, R. INFORMS Journal on Computing, 22(1): 81–92. 2010.
doi   link   bibtex   abstract  
On choosing parameters in retrospective-approximation algorithms for stochastic root finding and simulation optimization. Pasupathy, R. Operations Research, 58(4): 889–901. 2010.
On choosing parameters in retrospective-approximation algorithms for stochastic root finding and simulation optimization [pdf]Paper   doi   link   bibtex   abstract  
The Initial Transient in Steady-State Point Estimation: Contexts, A Bibliography, The MSE Criterion, and The MSER Statistic. Pasupathy, R.; and Schmeiser, B. W. In B.~Johansson; S.~Jain; J.~Montoya-Torres; J.~Hugan; and E.~Yücesan, editor(s), Proceedings of the 2010 Winter Simulation Conference, pages 184–197, Piscataway, NJ, 2010. Institute of Electrical and Electronics Engineers, Inc.
The Initial Transient in Steady-State Point Estimation: Contexts, A Bibliography, The MSE Criterion, and The MSER Statistic [pdf]Paper   link   bibtex   abstract  
Root Finding via DARTS: Dynamic Adaptive Random Target Shooting. Pasupathy, R.; and Schmeiser, B. W. In B.~Johansson; S.~Jain; J.~Montoya-Torres; J.~Hugan; and E.~Yücesan, editor(s), Proceedings of the 2010 Winter Simulation Conference, pages 1255–1262, Piscataway, NJ, 2010. Institute of Electrical and Electronics Engineers, Inc.
Root Finding via DARTS: Dynamic Adaptive Random Target Shooting [pdf]Paper   link   bibtex   abstract  
Selecting Small Quantiles. Pasupathy, R.; Szechtman, R.; and Yücesan, E. In B.~Johansson; S.~Jain; J.~Montoya-Torres; J.~Hugan; and E.~Yücesan, editor(s), Proceedings of the 2010 Winter Simulation Conference, pages 2762–2770, Piscataway, NJ, 2010. Institute of Electrical and Electronics Engineers, Inc.
Selecting Small Quantiles [pdf]Paper   link   bibtex   abstract  
Large-deviation sampling laws for constrained simulation optimization on finite sets. Hunter, S. R.; and Pasupathy, R. In B.~Johansson; S.~Jain; J.~Montoya-Torres; J.~Hugan; and E.~Yucesan, editor(s), Proceedings of the 2010 Winter Simulation Conference, pages 995–1002, Piscataway, NJ, 2010. Institute of Electrical and Electronics Engineers, Inc.
Large-deviation sampling laws for constrained simulation optimization on finite sets [pdf]Paper   link   bibtex   abstract  
  2009 (1)
Retrospective-approximation algorithms for multidimensional stochastic root-finding problems. Pasupathy, R.; and Schmeiser, B. W. ACM TOMACS, 19(2): 5:1–5:36. 2009.
Retrospective-approximation algorithms for multidimensional stochastic root-finding problems [pdf]Paper   doi   link   bibtex   abstract  
  undefined (2)
Risk-Efficient Sequential Simulation Estimators. Pasupathy, R.; and Yeh, Y. In Bae, K.; Feng, B.; Kim, S.; Lazarova-Molnar, S.; Zheng, Z.; Roeder, T.; and Thiesing, R., editor(s), Proceedings of the 2020 Winter Simulation Conference, Piscataway, NJ, . Institute of Electrical and Electronics Engineers, Inc.
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Retrospective Approximation for Smooth Stochastic Optimization. Newton, D.; Bollapragada, R.; Pasupathy, R.; and Yip, A. N. In OPT2020: 12-th Annual Workshop on Optimization for Machine Learning - NeurIPS, .
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