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subject:"Mathematische Optimierung"
~person:"Blanchet, Jose"
~source:"econis"
~subject:"Bayesian inference"
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Mathematische Optimierung
Bayesian inference
Probability theory
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3
Mathematical programming
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compound Poisson processes
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diffusion approximations
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distributionally robust optimization
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distributionally robust optimization using Wasserstein distances
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large deviations results
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model risk
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optimal transport
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Blanchet, Jose
Gallant, A. Ronald
9
Lo, Andrew W.
5
Montazerhodjat, Vahid
5
Geweke, John
4
Karni, Edi
4
Natarajan, Karthik
4
Robert, Christian P.
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Arieli, Itai
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Babichenko, Yakov
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Chamberlain, Gary
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Cheung, Yin-Wong
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Dickinson, David L.
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He, Shi
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Hoogerheide, Lennart F.
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Lahiri, Kajal
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Lisser, Abdel
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Ni, Weihong
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Norets, Andriy
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Pelenis, Justinas
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Prékopa, András
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Reid, Parker
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Sims, Christopher A.
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Yang, Liu
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Acharya, Srikumar
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Ackooij, Wim van
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Alfonsi, Aurélien
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Amengual, Dante
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Amir, Rabah
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Ansari, Asim
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Binmore, Ken
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Blanquero, Rafael
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Carrizosa, Emilio
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Chen, Xi
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Christer, Anthony H.
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Constantinescu, Corina
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Corbetta, Jacopo
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Cursi, Eduardo Souza de
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Dash, J. K.
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Mathematics of operations research
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Operations research
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ECONIS (ZBW)
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Sample out-of-sample inference based on Wasserstein distance
Blanchet, Jose
;
Kang, Yang
- In:
Operations research
69
(
2021
)
3
,
pp. 985-1013
Persistent link: https://www.econbiz.de/10012546913
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2
Quantifying distributional model risk via optimal transport
Blanchet, Jose
;
Murthy, Karthyek
- In:
Mathematics of operations research
44
(
2019
)
2
,
pp. 565-600
Persistent link: https://www.econbiz.de/10012028635
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