Here is a list of publications, listed in reverse order of publication. I also have a Google Scholar profile although the information there may not always be up-to-date.

- M.A. Khamis, R.R. Curtin, B. Moseley, H.Q. Ngo, X.L. Nguyen, D.
Olteanu, M. Schleich.
**"On functional aggregate queries with additive inequalities"**. Submitted to*The 2019 ACM SIGMOD/PODS International Conference on Management of Data*, 2019. [pdf] - R.R. Curtin, A.B. Gardner, S. Grzonkowski, A. Kleymenov, A.
Mosquera.
**"Detecting DGA domains with recurrent neural networks and side information"**. In preparation for submission to*The 16th Conference on Detection of Intrusions and Malware & Vulnerability Assessment*, 2019. - C. Sanderson, R.R. Curtin.
**"User-Friendly Sparse Matrices with Hybrid Storage and Template-Based Expression Optimisation"**. Submitted to*Mathematics in Computer Science (Special Issue from ICMS 2018)*, 2018. [pdf] [code] - S. Bhardwaj, R.R. Curtin, M. Edel, Y. Mentekidis, C. Sanderson.
**"ensmallen: a flexible C++ library for efficient function optimization"**,*Systems for ML Workshop at NeurIPS 2018*, 2018. [pdf] [bib] [code] - R.R. Curtin, M. Edel, M. Lozhnikov, Y. Mentekidis, S. Ghaisas, S.
Zhang.
**"mlpack 3: a fast, flexible machine learning library"**,*The Journal of Open Source Software*, vol. 3, issue 26, pp. 726, 2018. [pdf] [bib] [code] - C. Sanderson, R.R. Curtin.
**"A User-Friendly Hybrid Sparse Matrix Class in C++"**,*Proceedings of The 2018 International Congress on Mathematical Software (ICMS 2018)*, p. 422-430, 2018. [pdf] [bib][code] - R.R. Curtin, J. Echauz, A.B. Gardner.
**"Exploiting the structure of furthest neighbor search for fast approximate results"**,*Information Systems*, 2018. [pdf] [code] - C. Sanderson, R.R. Curtin.
**"gmm_diag and gmm_full: C++ classes for multi-threaded Gaussian mixture models and Expectation-Maximisation"**,*The Journal of Open Source Software*, vol. 2, 2017. [code] [paper] - C. Sanderson, R.R. Curtin.
**"An open source C++ implementation of multi-threaded Gaussian Mixture Models, k-means and expectation maximisation"**,*Proceedings of the 11th International Conference on Signal Processing and Communication Systems (ICSPCS 2017)*, p. 1-8. [code] - R.R. Curtin, M. Edel.
**"Designing and building the mlpack open-source machine learning library"**, submitted to*The Fourth International Conference of PUST (ICOPUST '17)*. [pdf] [code] - J. Echauz, A.B. Gardner, R.R. Curtin, N. Vasiloglou, G.J.
Vachtsevanos.
**"PFsuper: simulation-based prognostics to monitor and predict sparse time series"**, in*Annual Conference of the Prognostics and Health Management Society 2017 (PHM '17)*, 2017, p. 1--9. [pdf] - R. Feinman, R.R. Curtin, S. Shintre, A.B. Gardner.
**"Detecting adversarial samples from artifacts"**,*arXiv preprint arXiv:1703.00410*, 2017. [pdf] -
R.R. Curtin.
**A dual-tree algorithm for fast k-means clustering with large k"**, In*Proceedings of the 2017 SIAM International Conference on Data Mining (SDM '17)*, p. 300-308, 2017. 2017. [pdf] [code] -
C. Sanderson, R.R. Curtin.
**"Armadillo: a template-based C++ library for linear algebra"**,*Journal of Open Source Software*, vol. 1:26, pp. 1--2, 2016. [pdf] [bib] [code] -
R.R. Curtin, A.B. Gardner.
**"Fast approximate furthest neighbors with data-dependent candidate selection"**, in*Similarity Search and Applications 2016 (SISAP 2016)*, 2016, p. 221--235. [pdf] [bib] -
R.R. Curtin.
**"Improving dual-tree algorithms"**, Ph.D. thesis, Georgia Institute of Technology, 2015. [pdf] [bib] -
R.R. Curtin.
**"Faster dual-tree traversal for nearest neighbor search"**, in*Similarity Search and Applications (SISAP 2015)*, 2015, p. 77-89. [pdf] [bib] -
R.R. Curtin.
**"Single-tree GMM training"**, technical report GT-CSE-2015-01, Georgia Institute of Technology, School of Computational Science and Engineering, 2015. [pdf] [bib] -
S. Agrawal, R.R. Curtin, S. Ghaisas, M.R. Gupta.
**"Collaborative filtering via matrix decomposition in mlpack"**,*Workshop on Machine Learning Open Source Software 2015*, 2015. [pdf] [bib] [code] -
R.R. Curtin, D. Lee, W.B. March, P. Ram.
**"Plug-and-play runtime analysis for dual-tree algorithms"**, in*The Journal of Machine Learning Research*, vol. 16, p. 3269-3297, 2015. [pdf] [bib] -
M. Edel, A. Soni, R.R. Curtin.
**"An automatic benchmarking system"**, in*NIPS 2014 Workshop on Software Engineering for Machine Learning*, 2014. [pdf] [code] -
R.R. Curtin, W. Daley, D.V. Anderson.
**"Classifying broiler chicken condition using audio data"**, in*GlobalSIP 2014 Symposium on Signal Processing Applications Related to Animal Environments*, 2014. [pdf] [bib] -
R.R. Curtin, P. Ram,
**"Dual-tree fast max-kernel search"**,*Statistical Analysis and Data Mining*, vol. 7, issue 4, p. 229-253, 2014. [bib] [pdf] [code] -
R.R. Curtin, W.B. March, P. Ram, D.V. Anderson, A.G. Gray, C.L. Isbell,
Jr.,
**"Tree-independent dual-tree algorithms"**, in*The 30th International Conference on Machine Learning (ICML '13)*, Atlanta, Georgia, 2013. [bib] [pdf] -
R.R. Curtin, J.R. Cline, N.P. Slagle, W.B. March, P. Ram, N.A. Mehta,
A.G. Gray,
**"mlpack: a scalable C++ machine learning library"**,*The Journal of Machine Learning Research (JMLR)*, vol. 14, p. 801-805, 2013. [bib] [pdf] [code] -
R.R. Curtin, P. Ram, A.G. Gray,
**"Fast exact max-kernel search"**, in*SIAM Data Mining 2013 (SDM '13)*, Austin, Texas, 2013. [bib] [pdf] -
R.R. Curtin, J.R. Cline, N.P. Slagle, M.L. Amidon, A.G. Gray,
**"mlpack: a scalable C++ machine learning library"**, in*NIPS 2011 Workshop on Big Learning*, Granada, Spain, 2011. [bib] [pdf] [code] -
R.R. Curtin, N. Vasiloglou, D.V. Anderson,
**"Learning distances to improve phoneme classification"**, in*Proceedings of the 2011 IEEE International Workshop on Machine Learning in Signal Processing (MLSP 2011)*, Beijing, China, 2011. [bib] [pdf]