Nick Ryder

According to our database, Nick Ryder authored at least 11 papers between 2017 and 2023.

Collaborative distances:

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

2023

Bit Complexity of Jordan Normal Form and Polynomial Spectral Factorization.

Papri Dey, Ravi Kannan, Nick Ryder, Nikhil Srivastava

Proceedings of the 14th Innovations in Theoretical Computer Science Conference, 2023

2022

Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer.

Greg Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, Xiaodong Liu, David Farhi, Nick Ryder, Jakub Pachocki, Weizhu Chen, Jianfeng Gao

CoRR, 2022

2021

Bit Complexity of Jordan Normal Form and Spectral Factorization.

Papri Dey, Ravi Kannan, Nick Ryder, Nikhil Srivastava

CoRR, 2021

Evaluating Large Language Models Trained on Code.

Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Pondé de Oliveira Pinto, Jared Kaplan, Harrison Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Joshua Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, Wojciech Zaremba

CoRR, 2021

Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer.

Ge Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, Xiaodong Liu, David Farhi, Nick Ryder, Jakub Pachocki, Weizhu Chen, Jianfeng Gao

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

2020

Scaling Laws for Autoregressive Generative Modeling.

Tom Henighan, Jared Kaplan, Mor Katz, Mark Chen, Christopher Hesse, Jacob Jackson, Heewoo Jun, Tom B. Brown, Prafulla Dhariwal, Scott Gray, Chris Hallacy, Benjamin Mann, Alec Radford, Aditya Ramesh, Nick Ryder, Daniel M. Ziegler, John Schulman, Dario Amodei, Sam McCandlish

CoRR, 2020

Language Models are Few-Shot Learners.

Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Asymmetric Random Projections.

Nick Ryder, Zohar S. Karnin, Edo Liberty

CoRR, 2019

Exponential Lower Bounds on Spectrahedral Representations of Hyperbolicity Cones.

Prasad Raghavendra, Nick Ryder, Nikhil Srivastava, Benjamin Weitz

Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

2018

The geometry of rank decompositions of matrix multiplication II: 3×3 matrices.

Grey Ballard, Christian Ikenmeyer, J. M. Landsberg, Nick Ryder

CoRR, 2018

2017

Real Stability Testing.

Prasad Raghavendra, Nick Ryder, Nikhil Srivastava

Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017