Ryan R. Curtin

According to our database, Ryan R. Curtin authored at least 35 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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, Sangyeon Kim, Anjishnu Mukherjee, Nanubala Gnana Sai, Nippun Sharma, Yashwant Singh Parihar, Roshan Swain, Conrad Sanderson

J. Open Source Softw., February, 2023

Bandicoot: C++ Library for GPU Linear Algebra and Scientific Computing.

Ryan R. Curtin, Marcus Edel, Conrad Sanderson

CoRR, 2023

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

An Approximation Algorithm for the Matrix Tree Multiplication Problem.

Mahmoud Abo Khamis, Ryan R. Curtin, Sungjin Im, Benjamin Moseley, Hung Q. Ngo, Kirk Pruhs, Alireza Samadian

Proceedings of the 46th International Symposium on Mathematical Foundations of Computer Science, 2021

2020

Functional Aggregate Queries with Additive Inequalities.

Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich

ACM Trans. Database Syst., 2020

Flexible numerical optimization with ensmallen.

Ryan R. Curtin, Marcus Edel, Rahul Ganesh Prabhu, Suryoday Basak, Zhihao Lou, Conrad Sanderson

CoRR, 2020

An Adaptive Solver for Systems of Linear Equations.

Conrad Sanderson, Ryan R. Curtin

Proceedings of the 14th International Conference on Signal Processing and Communication Systems, 2020

Unconditional Coresets for Regularized Loss Minimization.

Alireza Samadian, Kirk Pruhs, Benjamin Moseley, Sungjin Im, Ryan R. Curtin

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Rk-means: Fast Clustering for Relational Data.

Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Exploiting the structure of furthest neighbor search for fast approximate results.

Ryan R. Curtin, Javier R. Echauz, Andrew B. Gardner

Inf. Syst., 2019

On Coresets for Regularized Loss Minimization.

Ryan R. Curtin, Sungjin Im, Benjamin Moseley, Kirk Pruhs, Alireza Samadian

CoRR, 2019

Detecting DGA domains with recurrent neural networks and side information.

Ryan R. Curtin, Andrew B. Gardner, Slawomir Grzonkowski, Alexey Kleymenov, Alejandro Mosquera

Proceedings of the 14th International Conference on Availability, Reliability and Security, 2019

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

User-Friendly Sparse Matrices with Hybrid Storage and Template-Based Expression Optimisation.

Conrad Sanderson, Ryan R. Curtin

CoRR, 2018

ensmallen: a flexible C++ library for efficient function optimization.

Shikhar Bhardwaj, Ryan R. Curtin, Marcus Edel, Yannis Mentekidis, Conrad Sanderson

CoRR, 2018

A User-Friendly Hybrid Sparse Matrix Class in C++.

Conrad Sanderson, Ryan R. Curtin

Proceedings of the Mathematical Software - ICMS 2018, 2018

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 generic and fast C++ optimization framework.

Ryan R. Curtin, Shikhar Bhardwaj, Marcus Edel, Yannis Mentekidis

CoRR, 2017

Designing and building the mlpack open-source machine learning library.

Ryan R. Curtin, Marcus Edel

CoRR, 2017

Detecting Adversarial Samples from Artifacts.

Reuben Feinman, Ryan R. Curtin, Saurabh Shintre, Andrew B. Gardner

CoRR, 2017

A Dual-Tree Algorithm for Fast <i>k</i>-means Clustering With Large <i>k</i>.

Ryan R. Curtin

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

An open source C++ implementation of multi-threaded Gaussian mixture models, k-means and expectation maximisation.

Conrad Sanderson, Ryan R. Curtin

Proceedings of the 11th International Conference on Signal Processing and Communication Systems, 2017

2016

Improving dual-tree algorithms.

Ryan R. Curtin

PhD thesis, 2016

Armadillo: a template-based C++ library for linear algebra.

Conrad Sanderson, Ryan R. Curtin

J. Open Source Softw., 2016

Fast approximate furthest neighbors with data-dependent hashing.

Ryan R. Curtin, Andrew B. Gardner

CoRR, 2016

Dual-tree $k$-means with bounded iteration runtime.

Ryan R. Curtin

CoRR, 2016

Fast Approximate Furthest Neighbors with Data-Dependent Candidate Selection.

Ryan R. Curtin, Andrew B. Gardner

Proceedings of the Similarity Search and Applications - 9th International Conference, 2016

2015

Plug-and-play dual-tree algorithm runtime analysis.

Ryan R. Curtin, Dongryeol Lee, William B. March, Parikshit Ram

J. Mach. Learn. Res., 2015

Faster Dual-Tree Traversal for Nearest Neighbor Search.

Ryan R. Curtin

Proceedings of the Similarity Search and Applications - 8th International Conference, 2015

2014

Dual-tree fast exact max-kernel search.

Ryan R. Curtin, Parikshit Ram

Stat. Anal. Data Min., 2014

Classifying broiler chicken condition using audio data.

Ryan R. Curtin, Wayne Daley, David V. Anderson

Proceedings of the 2014 IEEE Global Conference on Signal and Information Processing, 2014

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

Fast Exact Max-Kernel Search.

Ryan R. Curtin, Alexander G. Gray, Parikshit Ram

Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Tree-Independent Dual-Tree Algorithms.

Ryan R. Curtin, William B. March, Parikshit Ram, David V. Anderson, Alexander G. Gray, Charles L. Isbell Jr.

Proceedings of the 30th International Conference on Machine Learning, 2013

2011

Learning distances to improve phoneme classification.

Ryan R. Curtin, Nikolaos Vasiloglou, David V. Anderson

Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011