Tyler M. Tomita

According to our database, Tyler M. Tomita authored at least 10 papers between 2015 and 2025.

Collaborative distances:

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

2025

Simple Lifelong Learning Machines.

Joshua T. Vogelstein, Jayanta Dey, Hayden S. Helm, Will LeVine, Ronak D. Mehta, Tyler M. Tomita, Haoyin Xu, Ali Geisa, Qingyang Wang, Gido M. van de Ven, Chenyu Gao, Weiwei Yang, Bryan Tower, Jonathan Larson, Christopher M. White, Carey E. Priebe

IEEE Trans. Pattern Anal. Mach. Intell., November, 2025

2023

Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks.

Adam Li, Ronan Perry, Chester Huynh, Tyler M. Tomita, Ronak Mehta, Jesús Arroyo, Jesse Patsolic, Benjamin Falk, Sridevi V. Sarma, Joshua T. Vogelstein

SIAM J. Math. Data Sci., March, 2023

2022

Prospective Learning: Back to the Future.

Joshua T. Vogelstein, Timothy D. Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam S. Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael L. Platt, Lyle H. Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang

CoRR, 2022

2020

Sparse Projection Oblique Randomer Forests.

Tyler M. Tomita, James Browne, Cencheng Shen, Jaewon Chung, Jesse Patsolic, Benjamin Falk, Carey E. Priebe, Jason Yim, Randal C. Burns, Mauro Maggioni, Joshua T. Vogelstein

J. Mach. Learn. Res., 2020

Robust Similarity and Distance Learning via Decision Forests.

Tyler M. Tomita, Joshua T. Vogelstein

CoRR, 2020

2019

Manifold Forests: Closing the Gap on Neural Networks.

Ronan Perry, Tyler M. Tomita, Jesse Patsolic, Benjamin Falk, Joshua T. Vogelstein

CoRR, 2019

Forest Packing: Fast Parallel, Decision Forests.

James Browne, Disa Mhembere, Tyler M. Tomita, Joshua T. Vogelstein, Randal C. Burns

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

2017

A novel approach for selecting combination clinical markers of pathology applied to a large retrospective cohort of surgically resected pancreatic cysts.

David L. Masica, Marco Dal Molin, Christopher L. Wolfgang, Tyler M. Tomita, Mohammad R. Ostovaneh, Amanda Blackford, Robert A. Moran, Joanna K. Law, Thomas Barkley, Michael Goggins, Marcia Irene Canto, Meredith E. Pittman, James R. Eshleman, Syed Z. Ali, Elliot K. Fishman, Ihab R. Kamel, Siva P. Raman, Atif K. Zaheer, Nita Ahuja, Martin A. Makary, Matthew J. Weiss, Kenzo Hirose, John L. Cameron, Neda Rezaee, Jin He, Young Joon Ahn, Wenchuan Wu, Yuxuan Wang, Simeon Springer, Luis L. Diaz Jr., Nickolas Papadopoulos, Ralph H. Hruban, Kenneth W. Kinzler, Bert Vogelstein, Rachel Karchin, Anne Marie Lennon

J. Am. Medical Informatics Assoc., 2017

ROFLMAO: Robust Oblique Forests with Linear MAtrix Operations.

Tyler M. Tomita, Mauro Maggioni, Joshua T. Vogelstein

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

2015

Randomer Forests.

Tyler M. Tomita, Mauro Maggioni, Joshua T. Vogelstein

CoRR, 2015