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Enlu Zhou
Enlu Zhou
Professor, School of Industrial and Systems Engineering, Georgia Institute of Technology
Verified email at isye.gatech.edu - Homepage
Title
Cited by
Cited by
Year
Do unexpected panic attacks occur spontaneously?
AE Meuret, D Rosenfield, FH Wilhelm, E Zhou, A Conrad, T Ritz, WT Roth
Biological psychiatry 70 (10), 985-991, 2011
1122011
Solving continuous-state POMDPs via density projection
E Zhou, MC Fu, SI Marcus
IEEE Transactions on Automatic Control 55 (5), 1101-1116, 2010
1022010
Toward understanding the importance of noise in training neural networks
M Zhou, T Liu, Y Li, D Lin, E Zhou, T Zhao
International Conference on Machine Learning, 7594-7602, 2019
842019
Gradient-based adaptive stochastic search for non-differentiable optimization
E Zhou, J Hu
IEEE Transactions on Automatic Control 59 (7), 1818-1832, 2014
632014
The empirical likelihood approach to quantifying uncertainty in sample average approximation
H Lam, E Zhou
Operations Research Letters 45 (4), 301-307, 2017
622017
Robust ranking and selection with optimal computing budget allocation
S Gao, H Xiao, E Zhou, W Chen
Automatica 81, 30-36, 2017
612017
Change point analysis for longitudinal physiological data: detection of cardio-respiratory changes preceding panic attacks
D Rosenfield, E Zhou, FH Wilhelm, A Conrad, WT Roth, AE Meuret
Biological psychology 84 (1), 112-120, 2010
602010
Towards understanding the importance of shortcut connections in residual networks
T Liu, M Chen, M Zhou, SS Du, E Zhou, T Zhao
Advances in neural information processing systems 32, 2019
572019
Bayesian optimization of risk measures
S Cakmak, R Astudillo Marban, P Frazier, E Zhou
Advances in Neural Information Processing Systems 33, 20130-20141, 2020
552020
A survey of some model-based methods for global optimization
J Hu, Y Wang, E Zhou, MC Fu, SI Marcus
Optimization, Control, and Applications of Stochastic Systems: In Honor of …, 2012
492012
Sequential monte carlo simulated annealing
E Zhou, X Chen
Journal of Global Optimization 55, 101-124, 2013
462013
A particle filtering framework for randomized optimization algorithms
E Zhou, MC Fu, SI Marcus
2008 Winter Simulation Conference, 647-654, 2008
432008
Simulation optimization when facing input uncertainty
E Zhou, W Xie
2015 Winter Simulation Conference (WSC), 3714-3724, 2015
402015
Risk quantification in stochastic simulation under input uncertainty
H Zhu, T Liu, E Zhou
ACM Transactions on Modeling and Computer Simulation (TOMACS) 30 (1), 1-24, 2020
382020
A Bayesian risk approach to data-driven stochastic optimization: Formulations and asymptotics
D Wu, H Zhu, E Zhou
SIAM Journal on Optimization 28 (2), 1588-1612, 2018
382018
Efficient selection of a set of good enough designs with complexity preference
S Yan, E Zhou, CH Chen
IEEE Transactions on Automation Science and Engineering 9 (3), 596-606, 2012
332012
Robust multi-objective bayesian optimization under input noise
S Daulton, S Cakmak, M Balandat, MA Osborne, E Zhou, E Bakshy
International Conference on Machine Learning, 4831-4866, 2022
302022
Quantifying uncertainty in sample average approximation
H Lam, E Zhou
2015 Winter Simulation Conference (WSC), 3846-3857, 2015
302015
Weakly coupled dynamic program: Information and lagrangian relaxations
F Ye, H Zhu, E Zhou
IEEE Transactions on Automatic Control 63 (3), 698-713, 2017
262017
Particle filtering framework for a class of randomized optimization algorithms
E Zhou, MC Fu, SI Marcus
IEEE Transactions on Automatic Control 59 (4), 1025-1030, 2013
232013
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