Nan Du

According to our database, Nan Du authored at least 43 papers between 2012 and 2024.

Collaborative distances:

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

2024

Learning to Select the Best Forecasting Tasks for Clinical Outcome Prediction.

Yuan Xue, Nan Du, Anne Mottram, Martin Seneviratne, Andrew M. Dai

CoRR, 2024

Knowledge Graph Reasoning with Self-supervised Reinforcement Learning.

Ying Ma, Owen Burns, Mingqiu Wang, Gang Li, Nan Du, Laurent El Shafey, Liqiang Wang, Izhak Shafran, Hagen Soltau

CoRR, 2024

Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models.

Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Y. Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, Denny Zhou

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

PaLM: Scaling Language Modeling with Pathways.

Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel

J. Mach. Learn. Res., 2023

Learning to Skip for Language Modeling.

Dewen Zeng, Nan Du, Tao Wang, Yuanzhong Xu, Tao Lei, Zhifeng Chen, Claire Cui

CoRR, 2023

Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts.

Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Y. Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, Denny Zhou

CoRR, 2023

PaLM 2 Technical Report.

Rohan Anil, Andrew M. Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, Eric Chu, Jonathan H. Clark, Laurent El Shafey, Yanping Huang, Kathy Meier-Hellstern, Gaurav Mishra, Erica Moreira, Mark Omernick, Kevin Robinson, Sebastian Ruder, Yi Tay, Kefan Xiao, Yuanzhong Xu, Yujing Zhang, Gustavo Hernández Ábrego, Junwhan Ahn, Jacob Austin, Paul Barham, Jan A. Botha, James Bradbury, Siddhartha Brahma, Kevin Brooks, Michele Catasta, Yong Cheng, Colin Cherry, Christopher A. Choquette-Choo, Aakanksha Chowdhery, Clément Crepy, Shachi Dave, Mostafa Dehghani, Sunipa Dev, Jacob Devlin, Mark Díaz, Nan Du, Ethan Dyer, Vladimir Feinberg, Fangxiaoyu Feng, Vlad Fienber, Markus Freitag, Xavier Garcia, Sebastian Gehrmann, Lucas Gonzalez, et al.

CoRR, 2023

DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining.

Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu

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

Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference.

Tao Lei, Junwen Bai, Siddhartha Brahma, Joshua Ainslie, Kenton Lee, Yanqi Zhou, Nan Du, Vincent Y. Zhao, Yuexin Wu, Bo Li, Yu Zhang, Ming-Wei Chang

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

Lifelong Language Pretraining with Distribution-Specialized Experts.

Wuyang Chen, Yanqi Zhou, Nan Du, Yanping Huang, James Laudon, Zhifeng Chen, Claire Cui

Proceedings of the International Conference on Machine Learning, 2023

ReAct: Synergizing Reasoning and Acting in Language Models.

Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R. Narasimhan, Yuan Cao

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Massively Multilingual Shallow Fusion with Large Language Models.

Ke Hu, Tara N. Sainath, Bo Li, Nan Du, Yanping Huang, Andrew M. Dai, Yu Zhang, Rodrigo Cabrera, Zhifeng Chen, Trevor Strohman

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Designing Effective Sparse Expert Models.

Barret Zoph, Irwan Bello, Sameer Kumar, Nan Du, Yanping Huang, Jeff Dean, Noam Shazeer, William Fedus

CoRR, 2022

Mixture-of-Experts with Expert Choice Routing.

Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Y. Zhao, Andrew M. Dai, Zhifeng Chen, Quoc V. Le, James Laudon

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GLaM: Efficient Scaling of Language Models with Mixture-of-Experts.

Nan Du, Yanping Huang, Andrew M. Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, Barret Zoph, Liam Fedus, Maarten P. Bosma, Zongwei Zhou, Tao Wang, Yu Emma Wang, Kellie Webster, Marie Pellat, Kevin Robinson, Kathleen S. Meier-Hellstern, Toju Duke, Lucas Dixon, Kun Zhang, Quoc V. Le, Yonghui Wu, Zhifeng Chen, Claire Cui

Proceedings of the International Conference on Machine Learning, 2022

Finetuned Language Models are Zero-Shot Learners.

Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

R2D2: Relational Text Decoding with Transformers.

Aryan Arbabi, Mingqiu Wang, Laurent El Shafey, Nan Du, Izhak Shafran

CoRR, 2021

2020

Learning to Select Best Forecast Tasks for Clinical Outcome Prediction.

Yuan Xue, Nan Du, Anne Mottram, Martin Seneviratne, Andrew M. Dai

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

The Medical Scribe: Corpus Development and Model Performance Analyses.

Izhak Shafran, Nan Du, Linh Tran, Amanda Perry, Lauren Keyes, Mark Knichel, Ashley Domin, Lei Huang, Yuhui Chen, Gang Li, Mingqiu Wang, Laurent El Shafey, Hagen Soltau, Justin S. Paul

Proceedings of The 12th Language Resources and Evaluation Conference, 2020

Deep State-Space Generative Model For Correlated Time-to-Event Predictions.

Yuan Xue, Denny Zhou, Nan Du, Andrew M. Dai, Zhen Xu, Kun Zhang, Claire Cui

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

Deep Physiological State Space Model for Clinical Forecasting.

Yuan Xue, Denny Zhou, Nan Du, Andrew M. Dai, Zhen Xu, Kun Zhang, Claire Cui

CoRR, 2019

Learning to Infer Entities, Properties and their Relations from Clinical Conversations.

Nan Du, Mingqiu Wang, Linh Tran, Gang Li, Izhak Shafran

CoRR, 2019

Learning to Infer Entities, Properties and their Relations from Clinical Conversations.

Nan Du, Mingqiu Wang, Linh Tran, Gang Lee, Izhak Shafran

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Extracting Symptoms and their Status from Clinical Conversations.

Nan Du, Kai Chen, Anjuli Kannan, Linh Tran, Yuhui Chen, Izhak Shafran

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Learning Temporal Point Processes via Reinforcement Learning.

Shuang Li, Shuai Xiao, Shixiang Zhu, Nan Du, Yao Xie, Le Song

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks.

Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song

J. Mach. Learn. Res., 2017

2016

Modeling, learning, and inference of high-dimensional asynchronous event data.

Nan Du

PhD thesis, 2016

Influence Estimation and Maximization in Continuous-Time Diffusion Networks.

Manuel Gomez-Rodriguez, Le Song, Nan Du, Hongyuan Zha, Bernhard Schölkopf

ACM Trans. Inf. Syst., 2016

Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions.

Yichen Wang, Nan Du, Rakshit Trivedi, Le Song

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Recurrent Marked Temporal Point Processes: Embedding Event History to Vector.

Nan Du, Hanjun Dai, Rakshit Trivedi, Utkarsh Upadhyay, Manuel Gomez-Rodriguez, Le Song

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Isotonic Hawkes Processes.

Yichen Wang, Bo Xie, Nan Du, Le Song

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Time-Sensitive Recommendation From Recurrent User Activities.

Nan Du, Yichen Wang, Niao He, Jimeng Sun, Le Song

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams.

Nan Du, Mehrdad Farajtabar, Amr Ahmed, Alexander J. Smola, Le Song

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Constructing Disease Network and Temporal Progression Model via Context-Sensitive Hawkes Process.

Edward Choi, Nan Du, Robert Chen, Le Song, Jimeng Sun

Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades.

Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Mohammad Zamani, Nan Du, Hongyuan Zha, Le Song

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Shaping Social Activity by Incentivizing Users.

Mehrdad Farajtabar, Nan Du, Manuel Gomez-Rodriguez, Isabel Valera, Hongyuan Zha, Le Song

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning Time-Varying Coverage Functions.

Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Influence Function Learning in Information Diffusion Networks.

Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Continuous-Time Influence Maximization for Multiple Items.

Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song

CoRR, 2013

Scalable Influence Estimation in Continuous-Time Diffusion Networks.

Nan Du, Le Song, Manuel Gomez-Rodriguez, Hongyuan Zha

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Uncover Topic-Sensitive Information Diffusion Networks.

Nan Du, Le Song, Hyenkyun Woo, Hongyuan Zha

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Learning Networks of Heterogeneous Influence.

Nan Du, Le Song, Alexander J. Smola, Ming Yuan

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012