Learning distances to improve phoneme classification. - Ryan R. Curtin; Nikolaos Vasiloglou; David V. Anderson (MLSP, 2011)

Tree-Independent Dual-Tree Algorithms. - Ryan R. Curtin; William B. March; Parikshit Ram; David V. Anderson; Alexander G. Gray; Charles L. Isbell Jr. (ICML (3), 2013)

Fast Exact Max-Kernel Search. - Ryan R. Curtin; Alexander G. Gray; Parikshit Ram (SDM, 2013)

MLPACK: a scalable C++ machine learning library. - Ryan R. Curtin; James R. Cline; N. P. Slagle; William B. March; Parikshit Ram; Nishant A. Mehta; Alexander G. Gray (J. Mach. Learn. Res., 2013)

Classifying broiler chicken condition using audio data. - Ryan R. Curtin; Wayne Daley; David V. Anderson (GlobalSIP, 2014)

Dual-tree fast exact max-kernel search. - Ryan R. Curtin; Parikshit Ram (Stat. Anal. Data Min., 2014)

Faster Dual-Tree Traversal for Nearest Neighbor Search. - Ryan R. Curtin (SISAP, 2015)

Plug-and-play dual-tree algorithm runtime analysis. - Ryan R. Curtin; Dongryeol Lee; William B. March; Parikshit Ram (J. Mach. Learn. Res., 2015)

Fast Approximate Furthest Neighbors with Data-Dependent Candidate Selection. - Ryan R. Curtin; Andrew B. Gardner (SISAP, 2016)

Dual-tree $k$-means with bounded iteration runtime. - Ryan R. Curtin (CoRR, 2016)

Fast approximate furthest neighbors with data-dependent hashing. - Ryan R. Curtin; Andrew B. Gardner (CoRR, 2016)

Armadillo: a template-based C++ library for linear algebra. - Conrad Sanderson; Ryan R. Curtin (J. Open Source Softw., 2016)

Improving dual-tree algorithms. - Ryan R. Curtin (2016)

An open source C++ implementation of multi-threaded Gaussian mixture models, k-means and expectation maximisation. - Conrad Sanderson; Ryan R. Curtin (ICSPCS, 2017)

A Dual-Tree Algorithm for Fast k-means Clustering With Large k. - Ryan R. Curtin (SDM, 2017)

Detecting Adversarial Samples from Artifacts. - Reuben Feinman; Ryan R. Curtin; Saurabh Shintre; Andrew B. Gardner (CoRR, 2017)

Designing and building the mlpack open-source machine learning library. - Ryan R. Curtin; Marcus Edel (CoRR, 2017)

A generic and fast C++ optimization framework. - Ryan R. Curtin; Shikhar Bhardwaj; Marcus Edel; Yannis Mentekidis (CoRR, 2017)

gmm_diag and gmm_full: C++ classes for multi-threaded Gaussian mixture models and Expectation-Maximisation. - Conrad Sanderson; Ryan R. Curtin (J. Open Source Softw., 2017)

A User-Friendly Hybrid Sparse Matrix Class in C++. - Conrad Sanderson; Ryan R. Curtin (ICMS, 2018)

ensmallen: a flexible C++ library for efficient function optimization. - Shikhar Bhardwaj; Ryan R. Curtin; Marcus Edel; Yannis Mentekidis; Conrad Sanderson (CoRR, 2018)

User-Friendly Sparse Matrices with Hybrid Storage and Template-Based Expression Optimisation. - Conrad Sanderson; Ryan R. Curtin (CoRR, 2018)

mlpack 3: a fast, flexible machine learning library. - Ryan R. Curtin; Marcus Edel; Mikhail Lozhnikov; Yannis Mentekidis; Sumedh Ghaisas; Shangtong Zhang (J. Open Source Softw., 2018)

Detecting DGA domains with recurrent neural networks and side information. - Ryan R. Curtin; Andrew B. Gardner; Slawomir Grzonkowski; Alexey Kleymenov; Alejandro Mosquera (ARES, 2019)

On Coresets for Regularized Loss Minimization. - Ryan R. Curtin; Sungjin Im; Benjamin Moseley; Kirk Pruhs; Alireza Samadian (CoRR, 2019)

Exploiting the structure of furthest neighbor search for fast approximate results. - Ryan R. Curtin; Javier R. Echauz; Andrew B. Gardner (Inf. Syst., 2019)

Rk-means: Fast Clustering for Relational Data. - Ryan R. Curtin; Benjamin Moseley; Hung Q. Ngo 001; XuanLong Nguyen; Dan Olteanu; Maximilian Schleich (AISTATS, 2020)

Unconditional Coresets for Regularized Loss Minimization. - Alireza Samadian; Kirk Pruhs; Benjamin Moseley; Sungjin Im; Ryan R. Curtin (AISTATS, 2020)

An Adaptive Solver for Systems of Linear Equations. - Conrad Sanderson; Ryan R. Curtin (ICSPCS, 2020)

Flexible numerical optimization with ensmallen. - Ryan R. Curtin; Marcus Edel; Rahul Ganesh Prabhu; Suryoday Basak; Zhihao Lou; Conrad Sanderson (CoRR, 2020)

Functional Aggregate Queries with Additive Inequalities. - Mahmoud Abo Khamis; Ryan R. Curtin; Benjamin Moseley; Hung Q. Ngo 001; XuanLong Nguyen; Dan Olteanu; Maximilian Schleich (ACM Trans. Database Syst., 2020)

An Approximation Algorithm for the Matrix Tree Multiplication Problem. - Mahmoud Abo Khamis; Ryan R. Curtin; Sungjin Im; Benjamin Moseley; Hung Q. Ngo 001; Kirk Pruhs; Alireza Samadian (MFCS, 2021)

The ensmallen library for flexible numerical optimization. - Ryan R. Curtin; Marcus Edel; Rahul Ganesh Prabhu; Suryoday Basak; Zhihao Lou; Conrad Sanderson (J. Mach. Learn. Res., 2021)

Bandicoot: C++ Library for GPU Linear Algebra and Scientific Computing. - Ryan R. Curtin; Marcus Edel; Conrad Sanderson (CoRR, 2023)

mlpack 4: a fast, header-only C++ machine learning library. - Ryan R. Curtin; Marcus Edel; Omar Shrit; Shubham Agrawal; Suryoday Basak; James Joseph Balamuta; Ryan Birmingham; Kartik Dutt; Dirk Eddelbuettel; Rishabh Garg; Shikhar Jaiswal; Aakash Kaushik; et al. (J. Open Source Softw., 2023)

High-Dimensional Distributed Sparse Classification with Scalable Communication-Efficient Global Updates. - Fred Lu; Ryan R. Curtin; Edward Raff; Francis Ferraro; James Holt (KDD, 2024)

Optimizing the Optimal Weighted Average: Efficient Distributed Sparse Classification. - Fred Lu; Ryan R. Curtin; Edward Raff; Francis Ferraro; James Holt (CoRR, 2024)

Armadillo: an Efficient Framework for Numerical Linear Algebra. - Conrad Sanderson; Ryan R. Curtin (ICCAE, 2025)