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ORCIDQuoc V. Le
Quoc Viet Le – Quoc Le 0001
Person information
- affiliation: Google Inc., Mountain View, CA, USA
- affiliation: Stanford University, Computer Science Department, CA, USA
Other persons with the same name
- Quoc Le 0002 — Santa Clara University, School of Engineering, Department of Computer Engineering, CA, USA
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2020 – today
- 2023
[c143]Sheng Li, Garrett Andersen, Tao Chen, Liqun Cheng, Julian Grady, Da Huang, Quoc V. Le, Andrew Li, Xin Li, Yang Li, Chen Liang, Yifeng Lu, Yun Ni, Ruoming Pang, Mingxing Tan, Martin Wicke, Gang Wu, Shengqi Zhu, Parthasarathy Ranganathan, Norman P. Jouppi:
Hyperscale Hardware Optimized Neural Architecture Search. ASPLOS (3) 2023: 343-358- [i145]Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V. Le, Barret Zoph, Jason Wei, Adam Roberts:
The Flan Collection: Designing Data and Methods for Effective Instruction Tuning. CoRR abs/2301.13688 (2023) - [i144]Daiyi Peng, Xuanyi Dong, Esteban Real, Yifeng Lu, Quoc V. Le:
PyGlove: Efficiently Exchanging ML Ideas as Code. CoRR abs/2302.01918 (2023) - [i143]Qingqing Huang, Daniel S. Park, Tao Wang, Timo I. Denk, Andy Ly, Nanxin Chen, Zhengdong Zhang, Zhishuai Zhang, Jiahui Yu, Christian Havnø Frank, Jesse H. Engel, Quoc V. Le, William Chan, Wei Han:
Noise2Music: Text-conditioned Music Generation with Diffusion Models. CoRR abs/2302.03917 (2023) - [i142]Ryan Gillard, Stephen Jonany, Yingjie Miao, Michael Munn, Connal de Souza, Jonathan Dungay, Chen Liang, David R. So, Quoc V. Le, Esteban Real:
Unified Functional Hashing in Automatic Machine Learning. CoRR abs/2302.05433 (2023) - [i141]Xiangning Chen, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang, Yao Liu, Hieu Pham, Xuanyi Dong, Thang Luong, Cho-Jui Hsieh, Yifeng Lu, Quoc V. Le:
Symbolic Discovery of Optimization Algorithms. CoRR abs/2302.06675 (2023) - [i140]Jerry W. Wei, Le Hou, Andrew K. Lampinen, Xiangning Chen, Da Huang, Yi Tay, Xinyun Chen, Yifeng Lu, Denny Zhou, Tengyu Ma, Quoc V. Le:
Symbol tuning improves in-context learning in language models. CoRR abs/2305.08298 (2023) - [i139]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) - 2022
- [j11]David A. Patterson, Joseph Gonzalez, Urs Hölzle, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean:
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink. Computer 55(7): 18-28 (2022) - [j10]Yu Zhang
, Daniel S. Park, Wei Han, James Qin, Anmol Gulati, Joel Shor, Aren Jansen, Yuanzhong Xu, Yanping Huang, Shibo Wang, Zongwei Zhou, Bo Li, Min Ma, William Chan, Jiahui Yu, Yongqiang Wang, Liangliang Cao, Khe Chai Sim, Bhuvana Ramabhadran, Tara N. Sainath, Françoise Beaufays, Zhifeng Chen, Quoc V. Le, Chung-Cheng Chiu, Ruoming Pang, Yonghui Wu:
BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition. IEEE J. Sel. Top. Signal Process. 16(6): 1519-1532 (2022) - [c142]Dan Zhang, Safeen Huda, Ebrahim M. Songhori, Kartik Prabhu, Quoc V. Le, Anna Goldie, Azalia Mirhoseini:
A full-stack search technique for domain optimized deep learning accelerators. ASPLOS 2022: 27-42 - [c141]Yingwei Li, Adams Wei Yu, Tianjian Meng, Benjamin Caine, Jiquan Ngiam, Daiyi Peng, Junyang Shen, Yifeng Lu, Denny Zhou, Quoc V. Le, Alan L. Yuille, Mingxing Tan:
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection. CVPR 2022: 17161-17170 - [c140]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 - [c139]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 - [c138]Weizhe Hua, Zihang Dai, Hanxiao Liu, Quoc V. Le:
Transformer Quality in Linear Time. ICML 2022: 9099-9117 - [c137]Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, Denny Zhou:
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. NeurIPS 2022 - [c136]Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V. Le, Da Huang:
TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets. NeurIPS 2022 - [c135]Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Zhao, Andrew M. Dai, Zhifeng Chen, Quoc V. Le, James Laudon:
Mixture-of-Experts with Expert Choice Routing. NeurIPS 2022 - [c134]Gary Wang, Ekin D. Cubuk, Andrew Rosenberg, Shuyang Cheng, Ron J. Weiss, Bhuvana Ramabhadran, Pedro J. Moreno, Quoc V. Le, Daniel S. Park:
G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR. SLT 2022: 23-30 - [i138]Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Kathleen S. Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Aguera-Arcas, Claire Cui, Marian Croak, Ed H. Chi, Quoc Le:
LaMDA: Language Models for Dialog Applications. CoRR abs/2201.08239 (2022) - [i137]Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed H. Chi, Quoc Le, Denny Zhou:
Chain of Thought Prompting Elicits Reasoning in Large Language Models. CoRR abs/2201.11903 (2022) - [i136]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) - [i135]Weizhe Hua, Zihang Dai, Hanxiao Liu, Quoc V. Le:
Transformer Quality in Linear Time. CoRR abs/2202.10447 (2022) - [i134]Yingwei Li, Adams Wei Yu, Tianjian Meng, Benjamin Caine, Jiquan Ngiam, Daiyi Peng, Junyang Shen, Bo Wu, Yifeng Lu, Denny Zhou, Quoc V. Le, Alan L. Yuille, Mingxing Tan:
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection. CoRR abs/2203.08195 (2022) - [i133]Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou:
Self-Consistency Improves Chain of Thought Reasoning in Language Models. CoRR abs/2203.11171 (2022) - [i132]Tianjian Meng, Golnaz Ghiasi, Reza Mahjourian, Quoc V. Le, Mingxing Tan:
Revisiting Multi-Scale Feature Fusion for Semantic Segmentation. CoRR abs/2203.12683 (2022) - [i131]David A. Patterson, Joseph Gonzalez, Urs Hölzle, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean:
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink. CoRR abs/2204.05149 (2022) - [i130]Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V. Le, Da Huang:
Resource-Constrained Neural Architecture Search on Tabular Datasets. CoRR abs/2204.07615 (2022) - [i129]Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, Ed H. Chi:
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. CoRR abs/2205.10625 (2022) - [i128]Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou:
Rationale-Augmented Ensembles in Language Models. CoRR abs/2207.00747 (2022) - [i127]Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed H. Chi, Denny Zhou, Jason Wei:
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. CoRR abs/2210.09261 (2022) - [i126]Gary Wang, Ekin D. Cubuk, Andrew Rosenberg, Shuyang Cheng, Ron J. Weiss, Bhuvana Ramabhadran, Pedro J. Moreno, Quoc V. Le, Daniel S. Park:
G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR. CoRR abs/2210.10879 (2022) - [i125]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:
Transcending Scaling Laws with 0.1% Extra Compute. CoRR abs/2210.11399 (2022) - [i124]Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei:
Scaling Instruction-Finetuned Language Models. CoRR abs/2210.11416 (2022) - [i123]Jason Wei, Yi Tay, Quoc V. Le:
Inverse scaling can become U-shaped. CoRR abs/2211.02011 (2022) - 2021
- [j9]Azalia Mirhoseini, Anna Goldie, Mustafa Yazgan, Joe Wenjie Jiang, Ebrahim M. Songhori, Shen Wang, Young-Joon Lee, Eric Johnson, Omkar Pathak, Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, Jeff Dean:
A graph placement methodology for fast chip design. Nat. 594(7862): 207-212 (2021) - [c133]Hieu Pham, Quoc V. Le:
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks. AAAI 2021: 9351-9359 - [c132]Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph:
Simple Copy-Paste Is a Strong Data Augmentation Method for Instance Segmentation. CVPR 2021: 2918-2928 - [c131]Sheng Li, Mingxing Tan, Ruoming Pang, Andrew Li, Liqun Cheng, Quoc V. Le, Norman P. Jouppi:
Searching for Fast Model Families on Datacenter Accelerators. CVPR 2021: 8085-8095 - [c130]Hieu Pham, Zihang Dai, Qizhe Xie, Quoc V. Le:
Meta Pseudo Labels. CVPR 2021: 11557-11568 - [c129]Tu Vu, Minh-Thang Luong, Quoc V. Le, Grady Simon, Mohit Iyyer:
STraTA: Self-Training with Task Augmentation for Better Few-shot Learning. EMNLP (1) 2021: 5715-5731 - [c128]Golnaz Ghiasi, Barret Zoph, Ekin D. Cubuk, Quoc V. Le, Tsung-Yi Lin:
Multi-Task Self-Training for Learning General Representations. ICCV 2021: 8836-8845 - [c127]John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V. Le, Sergey Levine, Honglak Lee, Aleksandra Faust:
Evolving Reinforcement Learning Algorithms. ICLR 2021 - [c126]Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig:
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision. ICML 2021: 4904-4916 - [c125]Mingxing Tan, Quoc V. Le:
EfficientNetV2: Smaller Models and Faster Training. ICML 2021: 10096-10106 - [c124]Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc V. Le:
Towards Domain-Agnostic Contrastive Learning. ICML 2021: 10530-10541 - [c123]Arissa Wongpanich, Hieu Pham, James Demmel, Mingxing Tan, Quoc V. Le, Yang You, Sameer Kumar:
Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour. IPDPS Workshops 2021: 947-950 - [c122]Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan:
CoAtNet: Marrying Convolution and Attention for All Data Sizes. NeurIPS 2021: 3965-3977 - [c121]David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le:
Searching for Efficient Transformers for Language Modeling. NeurIPS 2021: 6010-6022 - [c120]Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le:
Pay Attention to MLPs. NeurIPS 2021: 9204-9215 - [i122]Hieu Pham, Quoc V. Le:
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks. CoRR abs/2101.01761 (2021) - [i121]John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc V. Le, Honglak Lee, Aleksandra Faust:
Evolving Reinforcement Learning Algorithms. CoRR abs/2101.03958 (2021) - [i120]Daiyi Peng, Xuanyi Dong, Esteban Real, Mingxing Tan, Yifeng Lu, Hanxiao Liu, Gabriel Bender, Adam Kraft, Chen Liang, Quoc V. Le:
PyGlove: Symbolic Programming for Automated Machine Learning. CoRR abs/2101.08809 (2021) - [i119]Sheng Li, Mingxing Tan, Ruoming Pang, Andrew Li, Liqun Cheng, Quoc V. Le, Norman P. Jouppi:
Searching for Fast Model Families on Datacenter Accelerators. CoRR abs/2102.05610 (2021) - [i118]Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig:
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision. CoRR abs/2102.05918 (2021) - [i117]Mingxing Tan, Quoc V. Le:
EfficientNetV2: Smaller Models and Faster Training. CoRR abs/2104.00298 (2021) - [i116]William Chan, Daniel S. Park, Chris A. Lee, Yu Zhang, Quoc V. Le, Mohammad Norouzi:
SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network. CoRR abs/2104.02133 (2021) - [i115]David A. Patterson, Joseph Gonzalez, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean:
Carbon Emissions and Large Neural Network Training. CoRR abs/2104.10350 (2021) - [i114]Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le:
Pay Attention to MLPs. CoRR abs/2105.08050 (2021) - [i113]Dan Zhang, Safeen Huda, Ebrahim M. Songhori, Quoc V. Le, Anna Goldie, Azalia Mirhoseini:
A Full-stack Accelerator Search Technique for Vision Applications. CoRR abs/2105.12842 (2021) - [i112]Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan:
CoAtNet: Marrying Convolution and Attention for All Data Sizes. CoRR abs/2106.04803 (2021) - [i111]Jacob Austin, Augustus Odena, Maxwell I. Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie J. Cai, Michael Terry, Quoc V. Le, Charles Sutton:
Program Synthesis with Large Language Models. CoRR abs/2108.07732 (2021) - [i110]Golnaz Ghiasi, Barret Zoph, Ekin D. Cubuk, Quoc V. Le, Tsung-Yi Lin:
Multi-Task Self-Training for Learning General Representations. CoRR abs/2108.11353 (2021) - [i109]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) - [i108]Tu Vu, Minh-Thang Luong, Quoc V. Le, Grady Simon, Mohit Iyyer:
STraTA: Self-Training with Task Augmentation for Better Few-shot Learning. CoRR abs/2109.06270 (2021) - [i107]David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le:
Primer: Searching for Efficient Transformers for Language Modeling. CoRR abs/2109.08668 (2021) - [i106]Yu Zhang, Daniel S. Park, Wei Han, James Qin, Anmol Gulati, Joel Shor, Aren Jansen, Yuanzhong Xu, Yanping Huang, Shibo Wang, Zongwei Zhou, Bo Li, Min Ma, William Chan, Jiahui Yu, Yongqiang Wang, Liangliang Cao, Khe Chai Sim, Bhuvana Ramabhadran, Tara N. Sainath, Françoise Beaufays, Zhifeng Chen, Quoc V. Le, Chung-Cheng Chiu, Ruoming Pang, Yonghui Wu:
BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition. CoRR abs/2109.13226 (2021) - [i105]Hieu Pham, Zihang Dai, Golnaz Ghiasi, Hanxiao Liu, Adams Wei Yu, Minh-Thang Luong, Mingxing Tan, Quoc V. Le:
Combined Scaling for Zero-shot Transfer Learning. CoRR abs/2111.10050 (2021) - [i104]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
- [c119]Cihang Xie, Mingxing Tan, Boqing Gong, Jiang Wang, Alan L. Yuille, Quoc V. Le:
Adversarial Examples Improve Image Recognition. CVPR 2020: 816-825 - [c118]Ekin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le:
Randaugment: Practical automated data augmentation with a reduced search space. CVPR Workshops 2020: 3008-3017 - [c117]Qizhe Xie, Minh-Thang Luong, Eduard H. Hovy, Quoc V. Le:
Self-Training With Noisy Student Improves ImageNet Classification. CVPR 2020: 10684-10695 - [c116]Mingxing Tan, Ruoming Pang, Quoc V. Le:
EfficientDet: Scalable and Efficient Object Detection. CVPR 2020: 10778-10787 - [c115]Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Golnaz Ghiasi, Mingxing Tan, Yin Cui, Quoc V. Le, Xiaodan Song:
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization. CVPR 2020: 11589-11598 - [c114]Bo Chen, Golnaz Ghiasi, Hanxiao Liu, Tsung-Yi Lin, Dmitry Kalenichenko, Hartwig Adam, Quoc V. Le:
MnasFPN: Learning Latency-Aware Pyramid Architecture for Object Detection on Mobile Devices. CVPR 2020: 13604-13613 - [c113]Gabriel Bender, Hanxiao Liu, Bo Chen, Grace Chu, Shuyang Cheng, Pieter-Jan Kindermans, Quoc V. Le:
Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS. CVPR 2020: 14311-14320 - [c112]Shuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang Song, Benjamin Caine, Vijay Vasudevan, Congcong Li, Quoc V. Le, Jonathon Shlens, Dragomir Anguelov:
Improving 3D Object Detection Through Progressive Population Based Augmentation. ECCV (21) 2020: 279-294 - [c111]Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le:
Learning Data Augmentation Strategies for Object Detection. ECCV (27) 2020: 566-583 - [c110]Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Yin Cui, Mingxing Tan, Quoc V. Le, Xiaodan Song:
Efficient Scale-Permuted Backbone with Learned Resource Distribution. ECCV (23) 2020: 572-586 - [c109]Jiahui Yu, Pengchong Jin, Hanxiao Liu, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Thomas S. Huang, Xiaodan Song, Ruoming Pang, Quoc Le:
BigNAS: Scaling up Neural Architecture Search with Big Single-Stage Models. ECCV (7) 2020: 702-717 - [c108]Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning:
Pre-Training Transformers as Energy-Based Cloze Models. EMNLP (1) 2020: 285-294 - [c107]Daniel S. Park, Yu Zhang, Chung-Cheng Chiu, Youzheng Chen, Bo Li, William Chan, Quoc V. Le, Yonghui Wu:
Specaugment on Large Scale Datasets. ICASSP 2020: 6879-6883 - [c106]Xinyun Chen, Chen Liang, Adams Wei Yu, Denny Zhou, Dawn Song, Quoc V. Le:
Neural Symbolic Reader: Scalable Integration of Distributed and Symbolic Representations for Reading Comprehension. ICLR 2020 - [c105]Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning:
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators. ICLR 2020 - [c104]Esteban Real, Chen Liang, David R. So, Quoc V. Le:
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch. ICML 2020: 8007-8019 - [c103]Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc V. Le, Qiang Liu, Dale Schuurmans:
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks. ICML 2020: 11546-11555 - [c102]Daniel S. Park, Yu Zhang, Ye Jia, Wei Han, Chung-Cheng Chiu, Bo Li, Yonghui Wu, Quoc V. Le:
Improved Noisy Student Training for Automatic Speech Recognition. INTERSPEECH 2020: 2817-2821 - [c101]Manas R. Joglekar, Cong Li, Mei Chen, Taibai Xu, Xiaoming Wang, Jay K. Adams, Pranav Khaitan, Jiahui Liu, Quoc V. Le:
Neural Input Search for Large Scale Recommendation Models. KDD 2020: 2387-2397 - [c100]Ekin Dogus Cubuk, Barret Zoph, Jonathon Shlens, Quoc Le:
RandAugment: Practical Automated Data Augmentation with a Reduced Search Space. NeurIPS 2020 - [c99]Zihang Dai, Guokun Lai, Yiming Yang, Quoc Le:
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing. NeurIPS 2020 - [c98]Hanxiao Liu, Andy Brock, Karen Simonyan, Quoc Le:
Evolving Normalization-Activation Layers. NeurIPS 2020 - [c97]Daiyi Peng, Xuanyi Dong, Esteban Real, Mingxing Tan, Yifeng Lu, Gabriel Bender, Hanxiao Liu, Adam Kraft, Chen Liang, Quoc Le:
PyGlove: Symbolic Programming for Automated Machine Learning. NeurIPS 2020 - [c96]Qizhe Xie, Zihang Dai, Eduard H. Hovy, Thang Luong, Quoc Le:
Unsupervised Data Augmentation for Consistency Training. NeurIPS 2020 - [c95]Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin Dogus Cubuk, Quoc Le:
Rethinking Pre-training and Self-training. NeurIPS 2020 - [i103]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:
Towards a Human-like Open-Domain Chatbot. CoRR abs/2001.09977 (2020) - [i102]Esteban Real, Chen Liang, David R. So, Quoc V. Le:
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch. CoRR abs/2003.03384 (2020) - [i101]Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning:
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators. CoRR abs/2003.10555 (2020) - [i100]Hieu Pham, Qizhe Xie, Zihang Dai, Quoc V. Le:
Meta Pseudo Labels. CoRR abs/2003.10580 (2020) - [i99]Jiahui Yu, Pengchong Jin, Hanxiao Liu, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Thomas S. Huang, Xiaodan Song, Ruoming Pang, Quoc V. Le:
BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models. CoRR abs/2003.11142 (2020) - [i98]Shuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang Song, Benjamin Caine, Vijay Vasudevan, Congcong Li, Quoc V. Le, Jonathon Shlens, Dragomir Anguelov:
Improving 3D Object Detection through Progressive Population Based Augmentation. CoRR abs/2004.00831 (2020) - [i97]Hanxiao Liu, Andrew Brock, Karen Simonyan, Quoc V. Le:
Evolving Normalization-Activation Layers. CoRR abs/2004.02967 (2020) - [i96]Azalia Mirhoseini, Anna Goldie, Mustafa Yazgan, Joe W. J. Jiang, Ebrahim M. Songhori, Shen Wang, Young-Joon Lee, Eric Johnson, Omkar Pathak, Sungmin Bae, Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Anand Babu, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, Jeff Dean:
Chip Placement with Deep Reinforcement Learning. CoRR abs/2004.10746 (2020) - [i95]Daniel S. Park, Yu Zhang, Ye Jia, Wei Han, Chung-Cheng Chiu, Bo Li, Yonghui Wu, Quoc V. Le:
Improved Noisy Student Training for Automatic Speech Recognition. CoRR abs/2005.09629 (2020) - [i94]Zihang Dai, Guokun Lai, Yiming Yang, Quoc V. Le:
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing. CoRR abs/2006.03236 (2020) - [i93]Xuanyi Dong, Mingxing Tan, Adams Wei Yu, Daiyi Peng, Bogdan Gabrys, Quoc V. Le:
AutoHAS: Differentiable Hyper-parameter and Architecture Search. CoRR abs/2006.03656 (2020) - [i92]Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin D. Cubuk, Quoc V. Le:
Rethinking Pre-training and Self-training. CoRR abs/2006.06882 (2020) - [i91]Cihang Xie, Mingxing Tan, Boqing Gong, Alan L. Yuille, Quoc V. Le:
Smooth Adversarial Training. CoRR abs/2006.14536 (2020) - [i90]Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc V. Le, Qiang Liu, Dale Schuurmans:
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks. CoRR abs/2007.00811 (2020) - [i89]Gabriel Bender, Hanxiao Liu, Bo Chen, Grace Chu, Shuyang Cheng, Pieter-Jan Kindermans, Quoc Le:
Can weight sharing outperform random architecture search? An investigation with TuNAS. CoRR abs/2008.06120 (2020) - [i88]Yu Zhang, James Qin, Daniel S. Park, Wei Han, Chung-Cheng Chiu, Ruoming Pang, Quoc V. Le, Yonghui Wu:
Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition. CoRR abs/2010.10504 (2020) - [i87]Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Yin Cui, Mingxing Tan, Quoc V. Le, Xiaodan Song:
Efficient Scale-Permuted Backbone with Learned Resource Distribution. CoRR abs/2010.11426 (2020) - [i86]Arissa Wongpanich, Hieu Pham, James Demmel, Mingxing Tan, Quoc V. Le, Yang You, Sameer Kumar:
Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour. CoRR abs/2011.00071 (2020) - [i85]Vikas Verma, Minh-Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc V. Le:
Towards Domain-Agnostic Contrastive Learning. CoRR abs/2011.04419 (2020) - [i84]