Create Citation & Research webpage

h2oai / h2o-3

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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Using the citation information provided on PUBDEV-2013, create a "How to cite H2O" webpage on the H2O website or somewhere in the code repo.

As a separate section or separate webpage, create a list of publications that cite H2O.

Here is a start to a list of publications that use H2O:

Normand R, Ferreira HA. (2015) Superchords: decoding EEG signals in the millisecond range. PeerJ PrePrints 3:e1549 [https://dx.doi.org/10.7287/peerj.preprints.1265v1]
Gilles Louppe, 2014. Understanding Random Forests: From Theory to Practice. PhD dissertation. [https://github.com/glouppe/phd-thesis|https://github.com/glouppe/phd-thesis]
Mentions H2O/Arno: [http://link.springer.com/book/10.1007/978-1-4842-1311-7|http://link.springer.com/book/10.1007/978-1-4842-1311-7]
"Deep Learning and Association Rule Mining for Predicting Drug Response in Cancer". The manuscript has been uploaded on bioRxiv and is available at the following link: http://dx.doi.org/10.1101/070490 The manuscript is currently under review for publication at Nature-Communications
http://www.rsm.nl/fileadmin/Images_NEW/ECFEB/The_value_of_points_of_interest_information.pdf
https://www.degruyter.com/downloadpdf/j/jwld.2016.30.issue-1/jwld-2016-0029/jwld-2016-0029.xml
Handbook of Big Data: https://www.crcpress.com/Handbook-of-Big-Data/Buhlmann-Drineas-Kane-van-der-Laan/p/book/9781482249071
[~accountid:557058:afd6e9a4-1891-4845-98ea-b5d34a2bc42c]'s dissertation: LeDell, E. (2015) Scalable Ensemble Learning and Computationally Efficient Variance Estimation (Doctoral Dissertation). University of California, Berkeley, USA. http://www.stat.berkeley.edu/~ledell/papers/ledell-phd-thesis.pdf
Computer Age Statistical Inference by Hastie and Efron https://web.stanford.edu/~hastie/CASI/

JIRA Issue Migration Info

Jira Issue: PUBDEV-2138 Assignee: Terone Ward Reporter: Erin LeDell State: Open Fix Version: N/A Attachments: Available (Count: 3) Development PRs: N/A

Attachments From Jira

Attachment Name: Deep Learning Anomaly Detection as Support Fraud Investigation in Brazilian Exports and Anti-Money Laundering.pdf Attached By: Vinod Iyengar File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-2138/Deep Learning Anomaly Detection as Support Fraud Investigation in Brazilian Exports and Anti-Money Laundering.pdf

Attachment Name: Identifying IT purchases anomalies in the Brazilian Government Procurement System using Deep Learning.pdf Attached By: Vinod Iyengar File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-2138/Identifying IT purchases anomalies in the Brazilian Government Procurement System using Deep Learning.pdf

Attachment Name: Predicting Recovery of Credit Operations on a Brazilian Bank.pdf Attached By: Vinod Iyengar File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-2138/Predicting Recovery of Credit Operations on a Brazilian Bank.pdf

h2oai / h2o-3

Create Citation & Research webpage #15056