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~subject:"Neuronale Netze"
~type_genre:"Graue Literatur"
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Neuronale Netze
Graph theory
264
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43
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43
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38
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ECONIS (ZBW)
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COIL : a deep architecture for column generation
Babaki, Behrouz
;
Charlin, Laurent
;
Jena, Sanjay Dominik
-
2022
Persistent link: https://www.econbiz.de/10013366318
Saved in:
2
Model-based graph reinforcement learning for inductive traffic signal control
Devailly, François-Xavier
;
Larocque, Denis
;
Charlin, …
-
2022
Persistent link: https://www.econbiz.de/10013410880
Saved in:
3
Machine learning for predicting stock return volatility
Filipović, Damir
;
Khalilzadeh, Amir
-
2021
We use machine learning methods to predict stock return volatility. Our out-of-sample prediction of realised volatility for a large cross-section of US stocks over the sample period from 1992 to 2016 is on average 44.1% against the actual realised volatility of 43.8% with an R2 being as high as...
Persistent link: https://www.econbiz.de/10012800743
Saved in:
4
Spatial regression graph convolutional neural networks : a deep learning paradigm for spatial multivariate distributions
Zhu, Di
;
Liu, Yu
;
Yao, Xin
;
Fischer, Manfred M.
-
2021
Persistent link: https://www.econbiz.de/10012816134
Saved in:
5
Application of machine learning in quantitative investment strategies on global stock markets
Grudniewicz, Jan
;
Ślepaczuk, Robert
-
2021
Persistent link: https://www.econbiz.de/10012816704
Saved in:
6
Machine learning advances for time series forecasting
Masini, Ricardo P.
;
Medeiros, Marcelo C.
;
Mendes, Eduardo F.
-
2020
networks, in their feed-forward and recurrent versions, and tree-based methods, such as random forests and boosted
trees
. We …
Persistent link: https://www.econbiz.de/10012390030
Saved in:
7
Data analytics for non-life insurance pricing
Wüthrich, Mario V.
;
Buser, Christoph
-
2017
-
Draft lecture notes, version January 27, 2017
regression
trees
, bagging, random forest, boosting machines and neural networks. Finally, we provide methodologies for analysing …
Persistent link: https://www.econbiz.de/10011625588
Saved in:
8
Artificial intelligence in asset management
Bartram, Söhnke M.
;
Branke, Jürgen
;
Motahari, Mehrshad
-
2020
-
This revision 01 April 2020
Persistent link: https://www.econbiz.de/10012217351
Saved in:
9
Double machine learning for treatment and causal parameters
Chernozhukov, Victor
;
Chetverikov, Denis
;
Demirer, Mert
; …
-
2016
random forests, lasso, ridge, deep neural nets, boosted
trees
, as well as various hybrids and aggregates of these methods (e …
Persistent link: https://www.econbiz.de/10011538313
Saved in:
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