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James C. Spall
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2020 – today
- 2024
- [c85]Shiqing Sun, James C. Spall:
Metropolis-Adjusted Langevin Algorithm with SPSA-Approximated Gradients. ACC 2024: 2734-2739 - [i4]Jiahao Shi, James C. Spall:
Difference Between Cyclic and Distributed Approach in Stochastic Optimization for Multi-agent System. CoRR abs/2409.05155 (2024) - 2023
- [c84]Ducheng Peng, Yiwen Chen, James C. Spall:
Formal Comparison of Simultaneous Perturbation Stochastic Approximation and Random Direction Stochastic Approximation ∗. ACC 2023: 744-749 - [c83]Shihong Wei, James C. Spall:
Quantifying the Estimation Error for a Constant-Gain Tracker. ACC 2023: 1629-1634 - [c82]James Cheng Peng, James C. Spall:
Performance Analysis of Model-Free Control and PID Control on a Class of Nonlinear MIMO Systems. CISS 2023: 1-6 - [c81]Shiqing Sun, James C. Spall:
Langevin Monte Carlo with SPSA-approximated Gradients. CISS 2023: 1-6 - 2022
- [j21]Zewei Li, James C. Spall:
Discrete Stochastic Optimization for Public Health Interventions with Constraints. Oper. Res. Forum 3(4) (2022) - [c80]Shihong Wei, James C. Spall:
Uncertainty Quantification for the Extended and the Deterministic-Gain Kalman Filters. ACC 2022: 2341-2346 - [i3]Zewei Li, James C. Spall:
Discrete Stochastic Optimization for Public Health Interventions with Constraints. CoRR abs/2206.13634 (2022) - 2021
- [c79]Jiahao Shi, James C. Spall:
SQP-based Projection SPSA Algorithm for Stochastic Optimization with Inequality Constraints. ACC 2021: 1244-1249 - [c78]Long Wang, James C. Spall:
Improved SPSA Using Complex Variables with Applications in Optimal Control Problems. ACC 2021: 3519-3524 - [c77]Shihong Wei, James C. Spall:
Probabilistic Bounds for a Class of Filtering Algorithms in the Scalar Case. ACC 2021: 4039-4044 - [c76]Long Wang, Jingyi Zhu, James C. Spall:
Model-Free Optimal Control using SPSA with Complex Variables. CISS 2021: 1-5 - [c75]Sihang Jiang, James C. Spall:
Comparison between Expected and Observed Fisher Information in Interval Estimation. CISS 2021: 1-6 - [c74]Shiqing Sun, James C. Spall:
Connection of Diagonal Hessian Estimates to Natural Gradients in Stochastic Optimization. CISS 2021: 1-6 - [c73]Xuan Wu, James C. Spall:
Improved Monte Carlo Estimation of the Fisher Information Matrix with Independent Perturbations. CISS 2021: 1-5 - 2020
- [j20]Jingyi Zhu
, Long Wang
Efficient Implementation of Second-Order Stochastic Approximation Algorithms in High-Dimensional Problems. IEEE Trans. Neural Networks Learn. Syst. 31(8): 3087-3099 (2020) - [c72]Xiangyu Yuan, James C. Spall:
Confidence Intervals with Expected and Observed Fisher Information in the Scalar Case. ACC 2020: 2599-2604 - [c71]Long Wang, James C. Spall:
Multilevel Data Integration with Application in Sensor Networks. ACC 2020: 5213-5218
2010 – 2019
- 2019
- [j19]Karla Hernandez, James C. Spall:
Generalization of a Result of Fabian on the Asymptotic Normality of Stochastic Approximation. Autom. 99: 420-424 (2019) - [c70]Ziyu Liu, Shihong Wei, James C. Spall:
Error Analysis for the Particle Filter. ACC 2019: 4515-4520 - [c69]Shiqing Sun, James C. Spall:
SPSA Method Using Diagonalized Hessian Estimate. CDC 2019: 4922-4927 - [c68]Shuyu Liu, Yingze Hou, James C. Spall:
Distribution Estimation for Stochastic Approximation in Finite Samples Using A Surrogate Stochastic Differential Equation Method. CISS 2019: 1-6 - [c67]Ziyu Liu, James C. Spall:
Error Estimation for the Particle Filter. CISS 2019: 1-6 - [i2]Jingyi Zhu, Long Wang, James C. Spall:
Efficient Implementation of Second-Order Stochastic Approximation Algorithms in High-Dimensional Problems. CoRR abs/1906.09533 (2019) - 2018
- [c66]Long Wang
Combining Subsystem and Full System Data with Application to Cold-Formed Steel Shear Wall. ACC 2018: 272-277 - [c65]Long Wang
Mixed Simultaneous Perturbation Stochastic Approximation for Gradient-Free Optimization with Noisy Measurements. ACC 2018: 3774-3779 - [c64]Xilei Zhao
A Markovian Framework for Modeling Dynamic Network Traffic. ACC 2018: 6616-6621 - [c63]Jingyi Zhu, James C. Spall:
Probabilistic Bounds in Tracking a Discrete-Time Varying Process. CDC 2018: 4849-4854 - [i1]Xilei Zhao, James C. Spall:
Modeling Traffic Networks Using Integrated Route and Link Data. CoRR abs/1811.01314 (2018) - 2017
- [c62]Long Wang
Beyond the identification of reliability for system with binary subsystems. ACC 2017: 158-163 - [c61]Lingyao Meng, James C. Spall:
Efficient computation of the Fisher information matrix in the EM algorithm. CISS 2017: 1-6 - 2016
- [c60]Carsten H. Botts, James C. Spall, Andrew J. Newman:
Multi-agent surveillance and tracking using cyclic stochastic gradient. ACC 2016: 270-275 - [c59]Xilei Zhao
Estimating travel time in urban traffic by modeling transportation network systems with binary subsystems. ACC 2016: 803-808 - [c58]Karla Hernandez, James C. Spall:
Asymptotic normality and efficiency analysis of the cyclic seesaw stochastic optimization algorithm. ACC 2016: 7255-7260 - [c57]Jingyi Zhu, James C. Spall:
Tracking capability of stochastic gradient algorithm with constant gain. CDC 2016: 4522-4527 - [c56]Pushpendre Rastogi, Jingyi Zhu, James C. Spall:
Efficient implementation of enhanced adaptive simultaneous perturbation algorithms. CISS 2016: 298-303 - 2015
- [c55]Karla Hernandez, James C. Spall:
System identification for multi-sensor data fusion. ACC 2015: 3931-3936 - [c54]Jingyi Zhu, James C. Spall:
Error bound analysis of the least-mean-squares algorithm in linear models. CISS 2015: 1-6 - [c53]Timothy H. Chung, James C. Spall:
Integrated stochastic optimization and statistical experimental design for multi-robot target tracking. WSC 2015: 2463-2474 - 2014
- [j18]James C. Spall:
Identification for Systems With Binary Subsystems. IEEE Trans. Autom. Control. 59(1): 3-17 (2014) - [c52]Qi Wang, James C. Spall:
Discrete simultaneous perturbation stochastic approximation for resource allocation in public health. ACC 2014: 3639-3644 - [c51]Karla Hernandez, James C. Spall:
Cyclic stochastic optimization with noisy function measurements. ACC 2014: 5204-5209 - 2013
- [c50]James C. Spall:
Parameter estimation for systems with binary subsystems. ACC 2013: 83-88 - [c49]Qi Wang, James C. Spall:
Rate of convergence analysis of discrete simultaneous perturbation stochastic approximation algorithm. ACC 2013: 4771-4776 - [c48]James C. Spall:
Maximum likelihood-based estimation of parameters in systems with binary subsystems. CISS 2013: 1-6 - 2012
- [j17]James C. Spall:
Cyclic Seesaw Process for Optimization and Identification. J. Optim. Theory Appl. 154(1): 187-208 (2012) - [c47]James C. Spall:
Asymptotic normality and uncertainty bounds for reliability estimates from subsystem and full system tests. ACC 2012: 56-61 - [c46]Xumeng Cao, James C. Spall:
Relative performance of expected and observed fisher information in covariance estimation for maximum likelihood estimates. ACC 2012: 1871-1876 - 2011
- [c45]Stacy D. Hill, James C. Spall, Coire J. Maranzano:
Inequality-based reliability estimates for complex systems. ACC 2011: 48-53 - [c44]Qi Wang, James C. Spall:
Discrete simultaneous perturbation stochastic approximation on loss function with noisy measurements. ACC 2011: 4520-4525 - [c43]James C. Spall:
Cyclic seesaw optimization and identification. CDC/ECC 2011: 4442-4447 - [c42]Coire J. Maranzano, James C. Spall:
Framework for estimating system reliability from full system and subsystem tests with dependence on dynamic inputs. CDC/ECC 2011: 6666-6671 - [c41]James C. Spall:
Cyclic seesaw optimization with applications to state-space model identification. CISS 2011: 1-6 - 2010
- [j16]Sonjoy Das, James C. Spall, Roger G. Ghanem
Efficient Monte Carlo computation of Fisher information matrix using prior information. Comput. Stat. Data Anal. 54(2): 272-289 (2010) - [c40]Coire J. Maranzano, James C. Spall:
Robust test design for reliability estimation with modeling error when combining full system and subsystem tests. ACC 2010: 3741-3746 - [c39]James C. Spall:
Convergence analysis for maximum likelihood-based reliability estimation from subsystem and full system tests. CDC 2010: 2017-2022 - [c38]Coire J. Maranzano, James C. Spall:
Implementation and application of maximum likelihood reliability estimation from subsystem and full system tests. PerMIS 2010: 146-153
2000 – 2009
- 2009
- [j15]James C. Spall:
Feedback and Weighting Mechanisms for Improving Jacobian Estimates in the Adaptive Simultaneous Perturbation Algorithm. IEEE Trans. Autom. Control. 54(6): 1216-1229 (2009) - [c37]David W. Hutchison, James C. Spall:
Stopping small-sample stochastic approximation. ACC 2009: 26-31 - [c36]James C. Spall:
System reliability estimation and confidence regions from subsystem and full system tests. ACC 2009: 5067-5072 - [c35]Xumeng Cao, James C. Spall:
Preliminary results on relative performance of expected and observed fisher information. CDC 2009: 1538-1543 - [c34]Xumeng Cao, James C. Spall:
Preliminary results in comparing the expected and observed Fisher information for maximum likelihood estimates. CISS 2009: 436-441 - [c33]James C. Spall:
On Monte Carlo methods for estimating the fisher information matrix in difficult problems. CISS 2009: 741-746 - [c32]Coire J. Maranzano, James C. Spall:
Optimum combination of full system and subsystem tests for estimating the reliability of a system. PerMIS 2009: 73-80 - 2008
- [j14]I-Jeng Wang, James C. Spall:
Stochastic optimisation with inequality constraints using simultaneous perturbations and penalty functions. Int. J. Control 81(8): 1232-1238 (2008) - [j13]Sonjoy Das, Roger G. Ghanem
Asymptotic Sampling Distribution for Polynomial Chaos Representation from Data: A Maximum Entropy and Fisher Information Approach. SIAM J. Sci. Comput. 30(5): 2207-2234 (2008) - [j12]Qing Song, James C. Spall, Yeng Chai Soh
Robust Neural Network Tracking Controller Using Simultaneous Perturbation Stochastic Approximation. IEEE Trans. Neural Networks 19(5): 817-835 (2008) - [c31]James C. Spall:
Improved methods for Monte Carlo estimation of the fisher information matrix. ACC 2008: 2395-2400 - [c30]James C. Spall:
Reliability estimation and confidence regions from subsystem and full system tests via maximum likelihood. PerMIS 2008: 9-16 - 2007
- [c29]Stacy D. Hill, James C. Spall:
Variance of Bounds in Inequality-Based Reliability Estimates. ACC 2007: 2320-2321 - [c28]Sonjoy Das, James C. Spall, Roger G. Ghanem
An efficient calculation of Fisher information matrix: Monte Carlo approach using prior information. CDC 2007: 963-968 - [c27]James C. Spall:
Feedback and Weighting Mechanisms for Improving Jacobian Estimates in the Adaptive Simultaneous Perturbation Algorithm. CISS 2007: 35-40 - [c26]Sonjoy Das, James C. Spall, Roger G. Ghanem
Efficient Monte Carlo computation of Fisher information matrix using prior information. PerMIS 2007: 242-249 - 2006
- [c25]James C. Spall:
Feedback and weighting mechanisms for improving Jacobian (Hessian) estimates in the adaptive simultaneous perturbation algorithm. ACC 2006: 1-6 - [c24]James C. Spall:
Seesaw method for combining parameter estimates. ACC 2006: 1-6 - [c23]Sonjoy Das, Roger G. Ghanem
Asymptotic Sampling Distribution for Polynomial Chaos Representation of Data: A Maximum Entropy and Fisher information approach. CDC 2006: 4139-4144 - [c22]James C. Spall:
Convergence Analysis for Feedback-and Weighting-Based Jacobian Estimates in the Adaptive Simultaneous Perturbation Algorithm. CDC 2006: 5669-5674 - 2005
- [c21]James C. Spall, Stacy D. Hill, David R. Stark:
Formal basis for algorithm comparisons in stochastic optimization. ACC 2005: 1545-1550 - [c20]David W. Hutchison, James C. Spall:
A Method for Stopping Nonconvergent Stochastic Approximation Processes. CDC/ECC 2005: 6620-6625 - 2004
- [j11]John L. Maryak, James C. Spall, Bryan D. Heydon:
Use of the Kalman filter for inference in state-space models with unknown noise distributions. IEEE Trans. Autom. Control. 49(1): 87-90 (2004) - [c19]James C. Spall:
Cramer-Rao bounds and Monte Carlo calculation of the Fisher information matrix in difficult problems. ACC 2004: 3140-3145 - [c18]Stacy D. Hill, James C. Spall:
Inequality-based estimates of systems reliability. ACC 2004: 4384-4387 - [c17]David W. Hutchison, James C. Spall:
Stochastic approximation in finite samples using surrogate processes. CDC 2004: 4157-4162 - 2003
- [b1]James C. Spall:
Introduction to stochastic search and optimization - estimation, simulation, and control. Wiley-Interscience series in discrete mathematics and optimization, Wiley 2003, ISBN 978-0-471-33052-3, pp. I-XX, 1-595 - [c16]David R. Stark, James C. Spall:
Rate of convergence in evolutionary computation. ACC 2003: 1932-1937 - [c15]James C. Spall:
Monte Carlo-based computation of the Fisher information matrix in nonstandard settings. ACC 2003: 3797-3802 - [c14]I-Jeng Wang, James C. Spall:
Stochastic optimization with inequality constraints using simultaneous perturbations and penalty functions. CDC 2003: 3808-3813 - [c13]Qing Song, James C. Spall, Yeng Chai Soh:
Robust neural network tracking controller using simultaneous perturbation stochastic approximation. CDC 2003: 6194-6199 - 2002
- [c12]James C. Spall:
Estimation via Markov chain Monte Carlo. ACC 2002: 2559-2564 - [c11]James C. Spall, Stacy D. Hill, David R. Stark:
Theoretical framework for comparing several popular stochastic optimization approaches. ACC 2002: 3153-3158 - 2001
- [c10]David R. Stark, James C. Spall:
Computable bounds on the rate of convergence in evolutionary computation. ACC 2001: 918-922 - 2000
- [j10]James C. Spall:
Adaptive stochastic approximation by the simultaneous perturbation method. IEEE Trans. Autom. Control. 45(10): 1839-1853 (2000) - [c9]James C. Spall, Stacy D. Hill, David R. Stark:
Some theoretical comparisons of stochastic optimization approaches. ACC 2000: 1904-1908 - [c8]Stacy D. Hill, James C. Spall:
Inequality-based reliability estimates for complex systems. ACC 2000: 2704-2705 - [c7]James C. Spall, Stacy D. Hill, David R. Stark:
First Results on Formal Comparison of Several Stochastic Optimization Algorithms. Annual Simulation Symposium 2000: 259-269
1990 – 1999
- 1999
- [j9]James C. Spall:
Review Of Stochastic Approximation Algorithms And Applications [Book Reviews]. Proc. IEEE 87(4): 688-690 (1999) - [j8]Payman Sadegh, James C. Spall:
Correction to "Optimal random perturbations for stochastic approximation using a simultaneous perturbation gradient approximation". IEEE Trans. Autom. Control. 44(1): 231-232 (1999) - [c6]James C. Spall, Stacy D. Hill, David R. Stark:
Theoretical comparisons of evolutionary computation and other optimization approaches. CEC 1999: 1398-1405 - [c5]James C. Spall:
Stochastic optimization and the simultaneous perturbation method. WSC 1999: 101-109 - 1998
- [j7]James C. Spall, John A. Cristion:
Model-free control of nonlinear stochastic systems with discrete-time measurements. IEEE Trans. Autom. Control. 43(9): 1198-1210 (1998) - [j6]Payman Sadegh, James C. Spall:
Optimal random perturbations for stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Trans. Autom. Control. 43(10): 1480-1484 (1998) - 1997
- [j5]James C. Spall:
A one-measurement form of simultaneous perturbation stochastic approximation. Autom. 33(1): 109-112 (1997) - [j4]James C. Spall, John A. Cristion:
A neural network controller for systems with unmodeled dynamics with applications to wastewater treatment. IEEE Trans. Syst. Man Cybern. Part B 27(3): 369-375 (1997) - 1996
- [c4]James C. Spall, John A. Cristion:
Model-free control of nonlinear stochastic systems in discrete time. ICNN 1996: 1859-1864 - [c3]James C. Spall, Mark S. Asher, John L. Maryak:
A neural network approach to nondestructive evaluation of complex structures, with application to highway bridges. ICNN 1996: 2154-2159 - 1995
- [j3]James C. Spall:
The Kantorovich inequality for error analysis of the Kalman filter with unknown noise distributions. Autom. 31(10): 1513-1517 (1995) - [j2]John L. Maryak, James C. Spall, Geoffrey L. Silberman:
Uncertainties for recursive estimators in nonlinear state-space models, with applications to epidemiology. Autom. 31(12): 1889-1892 (1995) - [c2]James C. Spall:
Stochastic Version of Second-Order (Newton-Raphson) Optimization Using only Function Measurements. WSC 1995: 347-352 - 1994
- [j1]Stacy D. Hill, James C. Spall:
Sensitivity of a Bayesian Analysis to the Prior Distribution. IEEE Trans. Syst. Man Cybern. Syst. 24(2): 216-221 (1994) - [c1]James C. Spall:
Developments in stochastic optimization algorithms with gradient approximations based on function measurements. WSC 1994: 207-214
Coauthor Index
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