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ORCIDJames M. Calvin
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2020 – today
- 2022
[j32]Cuicui Zheng, James M. Calvin
:
Convergence rate of a rectangular subdivision-based optimization algorithm for smooth multivariate functions. Optim. Lett. 16(4): 1137-1151 (2022)- 2021
- [j31]Cuicui Zheng, James M. Calvin, Craig Gotsman:
A DIRECT-type global optimization algorithm for image registration. J. Glob. Optim. 79(2): 431-445 (2021) - 2020
- [j30]James M. Calvin, Antanas Zilinskas:
On efficiency of a single variable bi-objective optimization algorithm. Optim. Lett. 14(1): 259-267 (2020)
2010 – 2019
- 2019
- [j29]Antanas Zilinskas, James M. Calvin:
Bi-objective decision making in global optimization based on statistical models. J. Glob. Optim. 74(4): 599-609 (2019) - [c19]Cuicui Zheng, James M. Calvin:
Using Simulation to Approximate the Minimum Cost of a Finite Set of Alternatives. WSC 2019: 3428-3435 - 2018
- [j28]James M. Calvin, Grazina Gimbutiene, William O. Phillips, Antanas Zilinskas:
On convergence rate of a rectangular partition based global optimization algorithm. J. Glob. Optim. 71(1): 165-191 (2018) - 2017
- [j27]James M. Calvin, Mario Hefter, André Herzwurm:
Adaptive approximation of the minimum of Brownian motion. J. Complex. 39: 17-37 (2017) - 2016
- [j26]James M. Calvin:
Probability Models in Global Optimization. Informatica 27(2): 323-334 (2016) - [p1]James M. Calvin:
On the Asymptotic Tractability of Global Optimization. Advances in Stochastic and Deterministic Global Optimization 2016: 3-12 - 2015
- [j25]James M. Calvin, Marvin K. Nakayama:
Resampled Regenerative Estimators. ACM Trans. Model. Comput. Simul. 25(4): 23:1-23:25 (2015) - 2014
- [j24]James M. Calvin, Antanas Zilinskas:
On a Global Optimization Algorithm for Bivariate Smooth Functions. J. Optim. Theory Appl. 163(2): 528-547 (2014) - 2013
- [c18]James M. Calvin, Marvin K. Nakayama:
Confidence intervals for quantiles with standardized time series. WSC 2013: 601-612 - 2012
- [j23]James M. Calvin, Yvonne Chen, Antanas Zilinskas:
An Adaptive Univariate Global Optimization Algorithm and Its Convergence Rate for Twice Continuously Differentiable Functions. J. Optim. Theory Appl. 155(2): 628-636 (2012) - 2011
- [j22]James M. Calvin:
An Adaptive Univariate Global Optimization Algorithm and Its Convergence Rate under the Wiener Measure. Informatica 22(4): 471-488 (2011) - [j21]James M. Calvin:
A lower bound on complexity of optimization under the r-fold integrated Wiener measure. J. Complex. 27(3-4): 404-416 (2011) - 2010
- [j20]James M. Calvin:
A lower bound on convergence rates of nonadaptive algorithms for univariate optimization with noise. J. Glob. Optim. 48(1): 17-27 (2010) - [j19]James M. Calvin:
Randomized algorithm for global optimization with bounded memory. Math. Comput. Simul. 80(6): 1068-1081 (2010)
2000 – 2009
- 2009
- [j18]James M. Calvin:
Simulation output analysis using integrated paths II: Low bias estimators. ACM Trans. Model. Comput. Simul. 19(3): 11:1-11:28 (2009) - [r1]James M. Calvin:
Adaptive Global Search. Encyclopedia of Optimization 2009: 19-21 - 2007
- [j17]James M. Calvin:
A lower bound on complexity of optimization on the Wiener space. Theor. Comput. Sci. 383(2-3): 132-139 (2007) - [j16]James M. Calvin:
Simulation output analysis using integrated paths. ACM Trans. Model. Comput. Simul. 17(3): 13 (2007) - [c17]James M. Calvin:
Low bias integrated path estimators. WSC 2007: 303-307 - 2006
- [j15]James M. Calvin, Marvin K. Nakayama:
Permuted Standardized Time Series for Steady-State Simulations. Math. Oper. Res. 31(2): 351-368 (2006) - [j14]James M. Calvin, Peter W. Glynn, Marvin K. Nakayama:
The semi-regenerative method of simulation output analysis. ACM Trans. Model. Comput. Simul. 16(3): 280-315 (2006) - [c16]James M. Calvin:
Experimental evaluation of integrated path estimators. WSC 2006: 329-332 - 2005
- [j13]David L. J. Alexander, David W. Bulger, James M. Calvin, H. Edwin Romeijn, Ryan L. Sherriff:
Approximate Implementations of Pure Random Search in the Presence of Noise. J. Glob. Optim. 31(4): 601-612 (2005) - 2004
- [j12]James M. Calvin, Marvin K. Nakayama:
Permuted derivative and importance-sampling estimators for regenerative simulations. Eur. J. Oper. Res. 156(2): 390-414 (2004) - [j11]James M. Calvin:
Lower bound on complexity of optimization of continuous functions. J. Complex. 20(5): 773-795 (2004) - [c15]James M. Calvin:
Simulation Output Analysis Based on Excursions. WSC 2004: 681-684 - [c14]James M. Calvin, Marvin K. Nakayama:
Permuted Weighted Area Estimators. WSC 2004: 721-727 - 2003
- [j10]James M. Calvin, Joseph Y.-T. Leung:
Average-case analysis of a greedy algorithm for the 0/1 knapsack problem. Oper. Res. Lett. 31(3): 202-210 (2003) - 2002
- [c13]James M. Calvin, Marvin K. Nakayama:
Output analysis: a comparison of output-analysis methods for simulations of processes with multiple regeneration sequences. WSC 2002: 328-335 - 2001
- [j9]James M. Calvin:
A One-Dimensional Optimization Algorithm and Its Convergence Rate under the Wiener Measure. J. Complex. 17(2): 306-344 (2001) - [j8]James M. Calvin, Antanas Zilinskas:
On Convergence of a P-Algorithm Based on a Statistical Model of Continuously Differentiable Functions. J. Glob. Optim. 19(3): 229-245 (2001) - [c12]James M. Calvin:
Efficient simulation for discrete path-dependent option pricing. WSC 2001: 325-328 - [c11]James M. Calvin, Marvin K. Nakayama:
Improving standardized time series methods by permuting path segments. WSC 2001: 348-353 - [c10]James M. Calvin, Peter W. Glynn, Marvin K. Nakayama:
Steady state simulation analysis: importance sampling using the semi-regenerative method. WSC 2001: 441-450 - 2000
- [j7]James M. Calvin, Marvin K. Nakayama:
Central Limit Theorems for Permuted Regenerative Estimators. Oper. Res. 48(5): 776-787 (2000)
1990 – 1999
- 1999
- [j6]Hisham A. Al-Mharmah, James M. Calvin:
Comparison of One-dimensional Composite and Non-composite Passive Algorithms. J. Glob. Optim. 15(2): 169-180 (1999) - [c9]James M. Calvin, Peter W. Glynn, Marvin K. Nakayama:
On the small-sample optimality of multiple-regeneration estimators. WSC 1999: 655-661 - [c8]James M. Calvin:
Polynomial acceleration of Monte-Carlo global search. WSC 1999: 673-677 - 1998
- [j5]James M. Calvin, Marvin K. Nakayama:
Using Permutations in Regenerative Simulations to Reduce Variance. ACM Trans. Model. Comput. Simul. 8(2): 153-193 (1998) - [c7]James M. Calvin, Marvin K. Nakayama:
Exploiting Multiple Regeneration Sequences in Simulation Output Analysis. WSC 1998: 695-700 - 1997
- [c6]James M. Calvin, Marvin K. Nakayama:
A New Variance-Reduction Technique for Regenerative Simulations of Markov Chains. WSC 1997: 224-229 - [c5]Hisham A. Al-Mharmah, James M. Calvin:
Comparison of Monte Carlo and Deterministic Methods for Non-Adaptive Optimization. WSC 1997: 348-351 - 1996
- [j4]Amar Ramudhin, John J. Bartholdi III, James M. Calvin, John H. Vande Vate, Gideon Weiss:
A Probabilistic Analysis of Two-Machine Flowshops. Oper. Res. 44(6): 899-908 (1996) - [j3]Hisham A. Al-Mharmah, James M. Calvin:
Optimal random non-adaptive algorithm for global optimization of Brownian motion. J. Glob. Optim. 8(1): 81-90 (1996) - 1994
- [j2]James M. Calvin:
Return-State Independent Quantities in Regenerative Simulation. Oper. Res. 42(3): 531-542 (1994) - [c4]James M. Calvin:
Average performance of Monte Carlo and Quasi-Monte Carlo methods for global optimization. WSC 1994: 262-265 - [c3]Sigrún Andradóttir, James M. Calvin, Peter W. Glynn:
Increasing the frequency of regeneration for Markov processes. WSC 1994: 320-323 - 1993
- [j1]James M. Calvin:
Consistency of a myopic Bayesian algorithm for one-dimensional global optimization. J. Glob. Optim. 3(2): 223-232 (1993) - [c2]James M. Calvin, Alan Dickens, Bob Gaines, Paul Metzger, Dale Miller, Dan Owen:
The Simnet Virtual World Architecture. VRAIS 1993: 450-455
1980 – 1989
- 1988
- [c1]James M. Calvin:
Covariance of regenerative mean and variance estimators for Markov chains. WSC 1988: 473-475
Coauthor Index
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