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Nan Du 0002
Person information
- affiliation: Google
- affiliation (former): Georgia Institute of Technology, GA, USA
Other persons with the same name
- Nan Du (aka: Du Nan) — disambiguation page
- Nan Du 0001 — Baidu Research Big Data Lab, Sunnyvale, CA, USA (and 1 more)
- Nan Du 0003
— Meta Platform, Inc. (and 2 more)
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2020 – today
- 2024
- [c29]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:
Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models. ICLR 2024 - [i28]Ying Ma, Owen Burns, Mingqiu Wang, Gang Li, Nan Du, Laurent El Shafey, Liqiang Wang, Izhak Shafran, Hagen Soltau:
Knowledge Graph Reasoning with Self-supervised Reinforcement Learning. CoRR abs/2405.13640 (2024) - [i27]Yuan Xue, Nan Du, Anne Mottram, Martin Seneviratne, Andrew M. Dai:
Learning to Select the Best Forecasting Tasks for Clinical Outcome Prediction. CoRR abs/2407.19359 (2024) - [i26]Yuan Xue, Denny Zhou, Nan Du, Andrew M. Dai, Zhen Xu, Kun Zhang, Claire Cui:
Deep State-Space Generative Model For Correlated Time-to-Event Predictions. CoRR abs/2407.19371 (2024) - 2023
- [j3]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:
PaLM: Scaling Language Modeling with Pathways. J. Mach. Learn. Res. 24: 240:1-240:113 (2023) - [c28]Ke Hu, Tara N. Sainath, Bo Li, Nan Du, Yanping Huang, Andrew M. Dai, Yu Zhang, Rodrigo Cabrera, Zhifeng Chen, Trevor Strohman:
Massively Multilingual Shallow Fusion with Large Language Models. ICASSP 2023: 1-5 - [c27]Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R. Narasimhan, Yuan Cao:
ReAct: Synergizing Reasoning and Acting in Language Models. ICLR 2023 - [c26]Wuyang Chen, Yanqi Zhou, Nan Du, Yanping Huang, James Laudon, Zhifeng Chen, Claire Cui:
Lifelong Language Pretraining with Distribution-Specialized Experts. ICML 2023: 5383-5395 - [c25]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:
Brainformers: Trading Simplicity for Efficiency. ICML 2023: 42531-42542 - [c24]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:
Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference. NeurIPS 2023 - [c23]Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu:
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. NeurIPS 2023 - [i25]Ke Hu, Tara N. Sainath, Bo Li, Nan Du, Yanping Huang, Andrew M. Dai, Yu Zhang, Rodrigo Cabrera, Zhifeng Chen, Trevor Strohman:
Massively Multilingual Shallow Fusion with Large Language Models. CoRR abs/2302.08917 (2023) - [i24]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:
Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference. CoRR abs/2304.04947 (2023) - [i23]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.:
PaLM 2 Technical Report. CoRR abs/2305.10403 (2023) - [i22]Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu:
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. CoRR abs/2305.10429 (2023) - [i21]Wuyang Chen, Yanqi Zhou, Nan Du, Yanping Huang, James Laudon, Zhifeng Chen, Claire Cui:
Lifelong Language Pretraining with Distribution-Specialized Experts. CoRR abs/2305.12281 (2023) - [i20]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:
Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts. CoRR abs/2305.14705 (2023) - [i19]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:
Brainformers: Trading Simplicity for Efficiency. CoRR abs/2306.00008 (2023) - [i18]Dewen Zeng, Nan Du, Tao Wang, Yuanzhong Xu, Tao Lei, Zhifeng Chen, Claire Cui:
Learning to Skip for Language Modeling. CoRR abs/2311.15436 (2023) - 2022
- [c22]Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le:
Finetuned Language Models are Zero-Shot Learners. ICLR 2022 - [c21]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:
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. ICML 2022: 5547-5569 - [c20]Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Y. Zhao, Andrew M. Dai, Zhifeng Chen, Quoc V. Le, James Laudon:
Mixture-of-Experts with Expert Choice Routing. NeurIPS 2022 - [i17]Barret Zoph, Irwan Bello, Sameer Kumar, Nan Du, Yanping Huang, Jeff Dean, Noam Shazeer, William Fedus:
Designing Effective Sparse Expert Models. CoRR abs/2202.08906 (2022) - [i16]Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Y. Zhao, Andrew M. Dai, Zhifeng Chen, Quoc Le, James Laudon:
Mixture-of-Experts with Expert Choice Routing. CoRR abs/2202.09368 (2022) - [i15]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:
PaLM: Scaling Language Modeling with Pathways. CoRR abs/2204.02311 (2022) - [i14]Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, Yuan Cao:
ReAct: Synergizing Reasoning and Acting in Language Models. CoRR abs/2210.03629 (2022) - 2021
- [i13]Aryan Arbabi, Mingqiu Wang, Laurent El Shafey, Nan Du, Izhak Shafran:
R2D2: Relational Text Decoding with Transformers. CoRR abs/2105.04645 (2021) - [i12]Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le:
Finetuned Language Models Are Zero-Shot Learners. CoRR abs/2109.01652 (2021) - [i11]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 Bosma, Zongwei Zhou, Tao Wang, Yu Emma Wang, Kellie Webster, Marie Pellat, Kevin Robinson, Kathy Meier-Hellstern, Toju Duke, Lucas Dixon, Kun Zhang, Quoc V. Le, Yonghui Wu, Zhifeng Chen, Claire Cui:
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. CoRR abs/2112.06905 (2021) - 2020
- [c19]Yuan Xue, Denny Zhou, Nan Du, Andrew M. Dai, Zhen Xu, Kun Zhang, Claire Cui:
Deep State-Space Generative Model For Correlated Time-to-Event Predictions. KDD 2020: 1552-1562 - [c18]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:
The Medical Scribe: Corpus Development and Model Performance Analyses. LREC 2020: 2036-2044 - [c17]Yuan Xue, Nan Du, Anne Mottram, Martin Seneviratne, Andrew M. Dai:
Learning to Select Best Forecast Tasks for Clinical Outcome Prediction. NeurIPS 2020 - [i10]Izhak Shafran, Nan Du, Linh Tran, Amanda Perry
The Medical Scribe: Corpus Development and Model Performance Analyses. CoRR abs/2003.11531 (2020)
2010 – 2019
- 2019
- [c16]Nan Du, Kai Chen, Anjuli Kannan, Linh Tran, Yuhui Chen, Izhak Shafran:
Extracting Symptoms and their Status from Clinical Conversations. ACL (1) 2019: 915-925 - [c15]Nan Du, Mingqiu Wang, Linh Tran, Gang Lee, Izhak Shafran:
Learning to Infer Entities, Properties and their Relations from Clinical Conversations. EMNLP/IJCNLP (1) 2019: 4978-4989 - [i9]Nan Du, Kai Chen, Anjuli Kannan, Linh Tran, Yuhui Chen, Izhak Shafran:
Extracting Symptoms and their Status from Clinical Conversations. CoRR abs/1906.02239 (2019) - [i8]Nan Du, Mingqiu Wang, Linh Tran, Gang Li, Izhak Shafran:
Learning to Infer Entities, Properties and their Relations from Clinical Conversations. CoRR abs/1908.11536 (2019) - [i7]Yuan Xue, Denny Zhou, Nan Du, Andrew M. Dai, Zhen Xu, Kun Zhang, Claire Cui:
Deep Physiological State Space Model for Clinical Forecasting. CoRR abs/1912.01762 (2019) - 2018
- [c14]Shuang Li, Shuai Xiao, Shixiang Zhu, Nan Du, Yao Xie, Le Song:
Learning Temporal Point Processes via Reinforcement Learning. NeurIPS 2018: 10804-10814 - [i6]Shuang Li, Shuai Xiao, Shixiang Zhu, Nan Du, Yao Xie, Le Song:
Learning Temporal Point Processes via Reinforcement Learning. CoRR abs/1811.05016 (2018) - 2017
- [j2]Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song:
Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks. J. Mach. Learn. Res. 18: 2:1-2:45 (2017) - 2016
- [b1]Nan Du:
Modeling, learning, and inference of high-dimensional asynchronous event data. Georgia Institute of Technology, Atlanta, GA, USA, 2016 - [j1]Manuel Gomez-Rodriguez
Influence Estimation and Maximization in Continuous-Time Diffusion Networks. ACM Trans. Inf. Syst. 34(2): 9:1-9:33 (2016) - [c13]Yichen Wang, Bo Xie, Nan Du, Le Song:
Isotonic Hawkes Processes. ICML 2016: 2226-2234 - [c12]Nan Du, Hanjun Dai, Rakshit Trivedi, Utkarsh Upadhyay, Manuel Gomez-Rodriguez
Recurrent Marked Temporal Point Processes: Embedding Event History to Vector. KDD 2016: 1555-1564 - [c11]Yichen Wang, Nan Du, Rakshit Trivedi, Le Song:
Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions. NIPS 2016: 4547-4555 - [i5]Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song:
Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks. CoRR abs/1612.02712 (2016) - 2015
- [c10]Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Mohammad Zamani, Nan Du, Hongyuan Zha, Le Song:
Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades. AISTATS 2015 - [c9]Edward Choi
Constructing Disease Network and Temporal Progression Model via Context-Sensitive Hawkes Process. ICDM 2015: 721-726 - [c8]Nan Du, Mehrdad Farajtabar, Amr Ahmed, Alexander J. Smola, Le Song:
Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams. KDD 2015: 219-228 - [c7]Nan Du, Yichen Wang, Niao He, Jimeng Sun, Le Song:
Time-Sensitive Recommendation From Recurrent User Activities. NIPS 2015: 3492-3500 - [i4]Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Nan Du, Mohammad Zamani, Hongyuan Zha, Le Song:
Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades. CoRR abs/1501.06582 (2015) - 2014
- [c6]Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song:
Influence Function Learning in Information Diffusion Networks. ICML 2014: 2016-2024 - [c5]Mehrdad Farajtabar, Nan Du, Manuel Gomez-Rodriguez, Isabel Valera
Shaping Social Activity by Incentivizing Users. NIPS 2014: 2474-2482 - [c4]Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song:
Learning Time-Varying Coverage Functions. NIPS 2014: 3374-3382 - [i3]Mehrdad Farajtabar, Nan Du, Manuel Gomez-Rodriguez, Isabel Valera, Hongyuan Zha, Le Song:
Shaping Social Activity by Incentivizing Users. CoRR abs/1408.0406 (2014) - 2013
- [c3]Nan Du, Le Song, Hyenkyun Woo, Hongyuan Zha:
Uncover Topic-Sensitive Information Diffusion Networks. AISTATS 2013: 229-237 - [c2]Nan Du, Le Song, Manuel Gomez-Rodriguez, Hongyuan Zha:
Scalable Influence Estimation in Continuous-Time Diffusion Networks. NIPS 2013: 3147-3155 - [i2]Nan Du, Le Song, Manuel Gomez-Rodriguez, Hongyuan Zha:
Scalable Influence Estimation in Continuous-Time Diffusion Networks. CoRR abs/1311.3669 (2013) - [i1]Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song:
Continuous-Time Influence Maximization for Multiple Items. CoRR abs/1312.2164 (2013) - 2012
- [c1]Nan Du, Le Song, Alexander J. Smola, Ming Yuan:
Learning Networks of Heterogeneous Influence. NIPS 2012: 2789-2797
Coauthor Index
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last updated on 2024-11-15 20:37 CET by the dblp team
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