David R. So

According to our database, David R. So authored at least 15 papers between 2018 and 2023.

Collaborative distances:

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

2023

Unified Functional Hashing in Automatic Machine Learning.

Ryan Gillard, Stephen Jonany, Yingjie Miao, Michael Munn, Connal de Souza, Jonathan Dungay, Chen Liang, David R. So, Quoc V. Le, Esteban Real

CoRR, 2023

EvoPrompting: Language Models for Code-Level Neural Architecture Search.

Angelica Chen, David Dohan, David R. So

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

Brainformers: Trading Simplicity for Efficiency.

Yanqi Zhou, Nan Du, Yanping Huang, Daiyi Peng, Chang Lan, Da Huang, Siamak Shakeri, David R. So, Andrew M. Dai, Yifeng Lu, Zhifeng Chen, Quoc V. Le, Claire Cui, James Laudon, Jeff Dean

Proceedings of the International Conference on Machine Learning, 2023

Transcending Scaling Laws with 0.1% Extra Compute.

Yi Tay, Jason Wei, Hyung Won Chung, Vinh Q. Tran, David R. So, Siamak Shakeri, Xavier Garcia, Huaixiu Steven Zheng, Jinfeng Rao, Aakanksha Chowdhery, Denny Zhou, Donald Metzler, Slav Petrov, Neil Houlsby, Quoc V. Le, Mostafa Dehghani

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink.

David A. Patterson, Joseph Gonzalez, Urs Hölzle, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean

Computer, 2022

2021

Primer: Searching for Efficient Transformers for Language Modeling.

David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le

CoRR, 2021

Carbon Emissions and Large Neural Network Training.

David A. Patterson, Joseph Gonzalez, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean

CoRR, 2021

Searching for Efficient Transformers for Language Modeling.

David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le

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

Pay Attention to MLPs.

Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le

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

MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records.

Zhen Xu, David R. So, Andrew M. Dai

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Towards a Human-like Open-Domain Chatbot.

Daniel Adiwardana, Minh-Thang Luong, David R. So, Jamie Hall, Noah Fiedel, Romal Thoppilan, Zi Yang, Apoorv Kulshreshtha, Gaurav Nemade, Yifeng Lu, Quoc V. Le

CoRR, 2020

AutoML-Zero: Evolving Machine Learning Algorithms From Scratch.

Esteban Real, Chen Liang, David R. So, Quoc V. Le

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

The Evolved Transformer.

David R. So, Quoc V. Le, Chen Liang

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Classification of crystallization outcomes using deep convolutional neural networks.

Andrew E. Bruno, Patrick Charbonneau, Janet Newman, Edward H. Snell, David R. So, Vincent Vanhoucke, Shawn Williams, Julie Wilson

CoRR, 2018

Evolving modular neural sequence architectures with genetic programming.

David Dohan, David R. So, Quoc V. Le

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018