Ryan Theisen

According to our database, Ryan Theisen authored at least 9 papers between 2019 and 2023.

Collaborative distances:

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

2023

Preference Optimization for Molecular Language Models.

Ryan Park, Ryan Theisen, Navriti Sahni, Marcel Patek, Anna Cichonska, Rayees Rahman

CoRR, 2023

When are ensembles really effective?

Ryan Theisen, Hyunsuk Kim, Yaoqing Yang, Liam Hodgkinson, Michael W. Mahoney

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Test Accuracy vs. Generalization Gap: Model Selection in NLP without Accessing Training or Testing Data.

Yaoqing Yang, Ryan Theisen, Liam Hodgkinson, Joseph E. Gonzalez, Kannan Ramchandran, Charles H. Martin, Michael W. Mahoney

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data.

Yaoqing Yang, Ryan Theisen, Liam Hodgkinson, Joseph E. Gonzalez, Kannan Ramchandran, Charles H. Martin, Michael W. Mahoney

CoRR, 2022

2021

Taxonomizing local versus global structure in neural network loss landscapes.

Yaoqing Yang, Liam Hodgkinson, Ryan Theisen, Joe Zou, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Evaluating State-of-the-Art Classification Models Against Bayes Optimality.

Ryan Theisen, Huan Wang, Lav R. Varshney, Caiming Xiong, Richard Socher

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Good Classifiers are Abundant in the Interpolating Regime.

Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Good linear classifiers are abundant in the interpolating regime.

Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney

CoRR, 2020

2019

Global Capacity Measures for Deep ReLU Networks via Path Sampling.

Ryan Theisen, Jason M. Klusowski, Huan Wang, Nitish Shirish Keskar, Caiming Xiong, Richard Socher

CoRR, 2019