Quoc V. Le

According to our database, Quoc V. Le authored at least 232 papers between 2005 and 2024.

Collaborative distances:

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

2024

Solving olympiad geometry without human demonstrations.

Trieu H. Trinh, Yuhuai Wu, Quoc V. Le, He He, Thang Luong

Nat., January, 2024

Long-form factuality in large language models.

Jerry Wei, Chengrun Yang, Xinying Song, Yifeng Lu, Nathan Hu, Dustin Tran, Daiyi Peng, Ruibo Liu, Da Huang, Cosmo Du, Quoc V. Le

CoRR, 2024

Self-Discover: Large Language Models Self-Compose Reasoning Structures.

Pei Zhou, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, Huaixiu Steven Zheng

CoRR, 2024

2023

Combined scaling for zero-shot transfer learning.

Hieu Pham, Zihang Dai, Golnaz Ghiasi, Kenji Kawaguchi, Hanxiao Liu, Adams Wei Yu, Jiahui Yu, Yi-Ting Chen, Minh-Thang Luong, Yonghui Wu, Mingxing Tan, Quoc V. Le

Neurocomputing, October, 2023

AutoNumerics-Zero: Automated Discovery of State-of-the-Art Mathematical Functions.

Esteban Real, Yao Chen, Mirko Rossini, Connal de Souza, Manav Garg, Akhil Verghese, Moritz Firsching, Quoc V. Le, Ekin Dogus Cubuk, David H. Park

CoRR, 2023

Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses.

Xiao Ma, Swaroop Mishra, Ariel Liu, Sophie Su, Jilin Chen, Chinmay Kulkarni, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi

CoRR, 2023

Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models.

Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V. Le, Denny Zhou

CoRR, 2023

FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation.

Tu Vu, Mohit Iyyer, Xuezhi Wang, Noah Constant, Jerry W. Wei, Jason Wei, Chris Tar, Yun-Hsuan Sung, Denny Zhou, Quoc V. Le, Thang Luong

CoRR, 2023

Large Language Models as Optimizers.

Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, Xinyun Chen

CoRR, 2023

Simple synthetic data reduces sycophancy in large language models.

Jerry W. Wei, Da Huang, Yifeng Lu, Denny Zhou, Quoc V. Le

CoRR, 2023

FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search.

Jordan Dotzel, Gang Wu, Andrew Li, Muhammad Umar, Yun Ni, Mohamed S. Abdelfattah, Zhiru Zhang, Liqun Cheng, Martin G. Dixon, Norman P. Jouppi, Quoc V. Le, Sheng Li

CoRR, 2023

Symbolic Discovery of Optimization Algorithms.

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

CoRR, 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

Noise2Music: Text-conditioned Music Generation with Diffusion Models.

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

CoRR, 2023

PyGlove: Efficiently Exchanging ML Ideas as Code.

Daiyi Peng, Xuanyi Dong, Esteban Real, Yifeng Lu, Quoc V. Le

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

Symbolic Discovery of Optimization Algorithms.

Xiangning Chen, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang, Hieu Pham, Xuanyi Dong, Thang Luong, Cho-Jui Hsieh, Yifeng Lu, Quoc V. Le

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

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning.

Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V. Le, Barret Zoph, Jason Wei, Adam Roberts

Proceedings of the International Conference on Machine Learning, 2023

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Inverse Scaling Can Become U-Shaped.

Jason Wei, Najoung Kim, Yi Tay, Quoc V. Le

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

Symbol tuning improves in-context learning in language models.

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

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

Hyperscale Hardware Optimized Neural Architecture Search.

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

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

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

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition.

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

IEEE J. Sel. Top. Signal Process., 2022

Inverse scaling can become U-shaped.

Jason Wei, Yi Tay, Quoc V. Le

CoRR, 2022

Scaling Instruction-Finetuned Language Models.

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

CoRR, 2022

Rationale-Augmented Ensembles in Language Models.

Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou

CoRR, 2022

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, Ed H. Chi

CoRR, 2022

Resource-Constrained Neural Architecture Search on Tabular Datasets.

Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V. Le, Da Huang

CoRR, 2022

Revisiting Multi-Scale Feature Fusion for Semantic Segmentation.

Tianjian Meng, Golnaz Ghiasi, Reza Mahjourian, Quoc V. Le, Mingxing Tan

CoRR, 2022

Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou

CoRR, 2022

DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection.

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

CoRR, 2022

Chain of Thought Prompting Elicits Reasoning in Large Language Models.

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed H. Chi, Quoc Le, Denny Zhou

CoRR, 2022

LaMDA: Language Models for Dialog Applications.

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 Agüera y Arcas, Claire Cui, Marian Croak, Ed H. Chi, Quoc Le

CoRR, 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

G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR.

Gary Wang, Ekin D. Cubuk, Andrew Rosenberg, Shuyang Cheng, Ron J. Weiss, Bhuvana Ramabhadran, Pedro J. Moreno, Quoc V. Le, Daniel S. Park

Proceedings of the IEEE Spoken Language Technology Workshop, 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

TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets.

Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V. Le, Da Huang

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

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, Denny Zhou

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

Transformer Quality in Linear Time.

Weizhe Hua, Zihang Dai, Hanxiao Liu, Quoc V. Le

Proceedings of the International Conference on Machine Learning, 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

DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection.

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

A full-stack search technique for domain optimized deep learning accelerators.

Dan Zhang, Safeen Huda, Ebrahim M. Songhori, Kartik Prabhu, Quoc V. Le, Anna Goldie, Azalia Mirhoseini

Proceedings of the ASPLOS '22: 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Lausanne, Switzerland, 28 February 2022, 2022

2021

A graph placement methodology for fast chip design.

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

Nat., 2021

Combined Scaling for Zero-shot Transfer Learning.

Hieu Pham, Zihang Dai, Golnaz Ghiasi, Hanxiao Liu, Adams Wei Yu, Minh-Thang Luong, Mingxing Tan, Quoc V. Le

CoRR, 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

Program Synthesis with Large Language Models.

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

CoRR, 2021

A Full-stack Accelerator Search Technique for Vision Applications.

Dan Zhang, Safeen Huda, Ebrahim M. Songhori, Quoc V. Le, Anna Goldie, Azalia Mirhoseini

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

SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network.

William Chan, Daniel S. Park, Chris A. Lee, Yu Zhang, Quoc V. Le, Mohammad Norouzi

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

CoAtNet: Marrying Convolution and Attention for All Data Sizes.

Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan

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

Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour.

Arissa Wongpanich, Hieu Pham, James Demmel, Mingxing Tan, Quoc V. Le, Yang You, Sameer Kumar

Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops, 2021

Towards Domain-Agnostic Contrastive Learning.

Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc V. Le

Proceedings of the 38th International Conference on Machine Learning, 2021

EfficientNetV2: Smaller Models and Faster Training.

Mingxing Tan, Quoc V. Le

Proceedings of the 38th International Conference on Machine Learning, 2021

Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision.

Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig

Proceedings of the 38th International Conference on Machine Learning, 2021

Evolving Reinforcement Learning Algorithms.

John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V. Le, Sergey Levine, Honglak Lee, Aleksandra Faust

Proceedings of the 9th International Conference on Learning Representations, 2021

Multi-Task Self-Training for Learning General Representations.

Golnaz Ghiasi, Barret Zoph, Ekin D. Cubuk, Quoc V. Le, Tsung-Yi Lin

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

STraTA: Self-Training with Task Augmentation for Better Few-shot Learning.

Tu Vu, Minh-Thang Luong, Quoc V. Le, Grady Simon, Mohit Iyyer

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Meta Pseudo Labels.

Hieu Pham, Zihang Dai, Qizhe Xie, Quoc V. Le

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Simple Copy-Paste Is a Strong Data Augmentation Method for Instance Segmentation.

Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Searching for Fast Model Families on Datacenter Accelerators.

Sheng Li, Mingxing Tan, Ruoming Pang, Andrew Li, Liqun Cheng, Quoc V. Le, Norman P. Jouppi

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

AutoDropout: Learning Dropout Patterns to Regularize Deep Networks.

Hieu Pham, Quoc V. Le

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

2020

Towards Domain-Agnostic Contrastive Learning.

Vikas Verma, Minh-Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc V. Le

CoRR, 2020

Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition.

Yu Zhang, James Qin, Daniel S. Park, Wei Han, Chung-Cheng Chiu, Ruoming Pang, Quoc V. Le, Yonghui Wu

CoRR, 2020

Smooth Adversarial Training.

Cihang Xie, Mingxing Tan, Boqing Gong, Alan L. Yuille, Quoc V. Le

CoRR, 2020

AutoHAS: Differentiable Hyper-parameter and Architecture Search.

Xuanyi Dong, Mingxing Tan, Adams Wei Yu, Daiyi Peng, Bogdan Gabrys, Quoc V. Le

CoRR, 2020

Chip Placement with Deep Reinforcement Learning.

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

CoRR, 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

Rethinking Pre-training and Self-training.

Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin Dogus Cubuk, Quoc Le

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

Unsupervised Data Augmentation for Consistency Training.

Qizhe Xie, Zihang Dai, Eduard H. Hovy, Thang Luong, Quoc Le

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

PyGlove: Symbolic Programming for Automated Machine Learning.

Daiyi Peng, Xuanyi Dong, Esteban Real, Mingxing Tan, Yifeng Lu, Gabriel Bender, Hanxiao Liu, Adam Kraft, Chen Liang, Quoc Le

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

Evolving Normalization-Activation Layers.

Hanxiao Liu, Andy Brock, Karen Simonyan, Quoc Le

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

Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing.

Zihang Dai, Guokun Lai, Yiming Yang, Quoc Le

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

Neural Input Search for Large Scale Recommendation Models.

Manas R. Joglekar, Cong Li, Mei Chen, Taibai Xu, Xiaoming Wang, Jay K. Adams, Pranav Khaitan, Jiahui Liu, Quoc V. Le

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

Improved Noisy Student Training for Automatic Speech Recognition.

Daniel S. Park, Yu Zhang, Ye Jia, Wei Han, Chung-Cheng Chiu, Bo Li, Yonghui Wu, Quoc V. Le

Proceedings of the Interspeech 2020, 2020

Go Wide, Then Narrow: Efficient Training of Deep Thin Networks.

Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc V. Le, Qiang Liu, Dale Schuurmans

Proceedings of the 37th International Conference on Machine Learning, 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

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators.

Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning

Proceedings of the 8th International Conference on Learning Representations, 2020

Neural Symbolic Reader: Scalable Integration of Distributed and Symbolic Representations for Reading Comprehension.

Xinyun Chen, Chen Liang, Adams Wei Yu, Denny Zhou, Dawn Song, Quoc V. Le

Proceedings of the 8th International Conference on Learning Representations, 2020

Specaugment on Large Scale Datasets.

Daniel S. Park, Yu Zhang, Chung-Cheng Chiu, Youzheng Chen, Bo Li, William Chan, Quoc V. Le, Yonghui Wu

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Pre-Training Transformers as Energy-Based Cloze Models.

Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Learning Data Augmentation Strategies for Object Detection.

Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le

Proceedings of the Computer Vision - ECCV 2020, 2020

BigNAS: Scaling up Neural Architecture Search with Big Single-Stage Models.

Jiahui Yu, Pengchong Jin, Hanxiao Liu, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Thomas S. Huang, Xiaodan Song, Ruoming Pang, Quoc Le

Proceedings of the Computer Vision - ECCV 2020, 2020

Efficient Scale-Permuted Backbone with Learned Resource Distribution.

Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Yin Cui, Mingxing Tan, Quoc V. Le, Xiaodan Song

Proceedings of the Computer Vision - ECCV 2020, 2020

Improving 3D Object Detection Through Progressive Population Based Augmentation.

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

Proceedings of the Computer Vision - ECCV 2020, 2020

Adversarial Examples Improve Image Recognition.

Cihang Xie, Mingxing Tan, Boqing Gong, Jiang Wang, Alan L. Yuille, Quoc V. Le

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Self-Training With Noisy Student Improves ImageNet Classification.

Qizhe Xie, Minh-Thang Luong, Eduard H. Hovy, Quoc V. Le

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

EfficientDet: Scalable and Efficient Object Detection.

Mingxing Tan, Ruoming Pang, Quoc V. Le

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization.

Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Golnaz Ghiasi, Mingxing Tan, Yin Cui, Quoc V. Le, Xiaodan Song

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Randaugment: Practical automated data augmentation with a reduced search space.

Ekin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

MnasFPN: Learning Latency-Aware Pyramid Architecture for Object Detection on Mobile Devices.

Bo Chen, Golnaz Ghiasi, Hanxiao Liu, Tsung-Yi Lin, Dmitry Kalenichenko, Hartwig Adam, Quoc V. Le

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS.

Gabriel Bender, Hanxiao Liu, Bo Chen, Grace Chu, Shuyang Cheng, Pieter-Jan Kindermans, Quoc V. Le

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Natural Questions: a Benchmark for Question Answering Research.

Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur P. Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, Slav Petrov

Trans. Assoc. Comput. Linguistics, 2019

RandAugment: Practical data augmentation with no separate search.

Ekin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le

CoRR, 2019

Neural Input Search for Large Scale Recommendation Models.

Manas R. Joglekar, Cong Li, Jay K. Adams, Pranav Khaitan, Quoc V. Le

CoRR, 2019

Selfie: Self-supervised Pretraining for Image Embedding.

Trieu H. Trinh, Minh-Thang Luong, Quoc V. Le

CoRR, 2019

Unsupervised Data Augmentation.

Qizhe Xie, Zihang Dai, Eduard H. Hovy, Minh-Thang Luong, Quoc V. Le

CoRR, 2019

Using Videos to Evaluate Image Model Robustness.

Keren Gu, Brandon Yang, Jiquan Ngiam, Quoc V. Le, Jonathon Shlens

CoRR, 2019

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection.

Golnaz Ghiasi, Tsung-Yi Lin, Ruoming Pang, Quoc V. Le

CoRR, 2019

Soft Conditional Computation.

Brandon Yang, Gabriel Bender, Quoc V. Le, Jiquan Ngiam

CoRR, 2019

Mixtape: Breaking the Softmax Bottleneck Efficiently.

Zhilin Yang, Thang Luong, Ruslan Salakhutdinov, Quoc V. Le

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

XLNet: Generalized Autoregressive Pretraining for Language Understanding.

Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, Quoc V. Le

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

CondConv: Conditionally Parameterized Convolutions for Efficient Inference.

Brandon Yang, Gabriel Bender, Quoc V. Le, Jiquan Ngiam

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks.

Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism.

Yanping Huang, Youlong Cheng, Ankur Bapna, Orhan Firat, Dehao Chen, Mia Xu Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V. Le, Yonghui Wu, Zhifeng Chen

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Saccader: Improving Accuracy of Hard Attention Models for Vision.

Gamaleldin F. Elsayed, Simon Kornblith, Quoc V. Le

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition.

Daniel S. Park, William Chan, Yu Zhang, Chung-Cheng Chiu, Barret Zoph, Ekin D. Cubuk, Quoc V. Le

Proceedings of the Interspeech 2019, 2019

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

Mingxing Tan, Quoc V. Le

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

The Evolved Transformer.

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

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

The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study.

Daniel S. Park, Jascha Sohl-Dickstein, Quoc V. Le, Samuel L. Smith

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

Diversity and Depth in Per-Example Routing Models.

Prajit Ramachandran, Quoc V. Le

Proceedings of the 7th International Conference on Learning Representations, 2019

Searching for MobileNetV3.

Andrew Howard, Ruoming Pang, Hartwig Adam, Quoc V. Le, Mark Sandler, Bo Chen, Weijun Wang, Liang-Chieh Chen, Mingxing Tan, Grace Chu, Vijay Vasudevan, Yukun Zhu

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Attention Augmented Convolutional Networks.

Irwan Bello, Barret Zoph, Quoc Le, Ashish Vaswani, Jonathon Shlens

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

MnasNet: Platform-Aware Neural Architecture Search for Mobile.

Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, Quoc V. Le

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Do Better ImageNet Models Transfer Better?

Simon Kornblith, Jonathon Shlens, Quoc V. Le

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection.

Golnaz Ghiasi, Tsung-Yi Lin, Quoc V. Le

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

AutoAugment: Learning Augmentation Strategies From Data.

Ekin D. Cubuk, Barret Zoph, Dandelion Mané, Vijay Vasudevan, Quoc V. Le

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

MixConv: Mixed Depthwise Convolutional Kernels.

Mingxing Tan, Quoc V. Le

Proceedings of the 30th British Machine Vision Conference 2019, 2019

Transformer-XL: Attentive Language Models beyond a Fixed-Length Context.

Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc Viet Le, Ruslan Salakhutdinov

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

BAM! Born-Again Multi-Task Networks for Natural Language Understanding.

Kevin Clark, Minh-Thang Luong, Urvashi Khandelwal, Christopher D. Manning, Quoc V. Le

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

Regularized Evolution for Image Classifier Architecture Search.

Esteban Real, Alok Aggarwal, Yanping Huang, Quoc V. Le

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Scalable and accurate deep learning with electronic health records.

Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Michaela Hardt, Peter J. Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Yi Zhang, Gerardo Flores, Gavin E. Duggan, Jamie Irvine, Quoc Le, Kurt Litsch, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Gregory S. Corrado, Jeffrey Dean

npj Digit. Medicine, 2018

Domain Adaptive Transfer Learning with Specialist Models.

Jiquan Ngiam, Daiyi Peng, Vijay Vasudevan, Simon Kornblith, Quoc V. Le, Ruoming Pang

CoRR, 2018

GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism.

Yanping Huang, Yonglong Cheng, Dehao Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V. Le, Zhifeng Chen

CoRR, 2018

Backprop Evolution.

Maximilian Alber, Irwan Bello, Barret Zoph, Pieter-Jan Kindermans, Prajit Ramachandran, Quoc V. Le

CoRR, 2018

MnasNet: Platform-Aware Neural Architecture Search for Mobile.

Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Quoc V. Le

CoRR, 2018

Memory Augmented Policy Optimization for Program Synthesis with Generalization.

Chen Liang, Mohammad Norouzi, Jonathan Berant, Quoc V. Le, Ni Lao

CoRR, 2018

Stochastic natural gradient descent draws posterior samples in function space.

Samuel L. Smith, Daniel Duckworth, Quoc V. Le, Jascha Sohl-Dickstein

CoRR, 2018

A Simple Method for Commonsense Reasoning.

Trieu H. Trinh, Quoc V. Le

CoRR, 2018

AutoAugment: Learning Augmentation Policies from Data.

Ekin Dogus Cubuk, Barret Zoph, Dandelion Mané, Vijay Vasudevan, Quoc V. Le

CoRR, 2018

Scalable and accurate deep learning for electronic health records.

Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Peter J. Liu, Xiaobing Liu, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Gavin E. Duggan, Gerardo Flores, Michaela Hardt, Jamie Irvine, Quoc V. Le, Kurt Litsch, Jake Marcus, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Greg Corrado, Jeff Dean

CoRR, 2018

Neural Program Synthesis with Priority Queue Training.

Daniel A. Abolafia, Mohammad Norouzi, Quoc V. Le

CoRR, 2018

Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing.

Chen Liang, Mohammad Norouzi, Jonathan Berant, Quoc V. Le, Ni Lao

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

DropBlock: A regularization method for convolutional networks.

Golnaz Ghiasi, Tsung-Yi Lin, Quoc V. Le

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

Learning Longer-term Dependencies in RNNs with Auxiliary Losses.

Trieu H. Trinh, Andrew M. Dai, Thang Luong, Quoc V. Le

Proceedings of the 35th International Conference on Machine Learning, 2018

Efficient Neural Architecture Search via Parameter Sharing.

Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, Jeff Dean

Proceedings of the 35th International Conference on Machine Learning, 2018

Understanding and Simplifying One-Shot Architecture Search.

Gabriel Bender, Pieter-Jan Kindermans, Barret Zoph, Vijay Vasudevan, Quoc V. Le

Proceedings of the 35th International Conference on Machine Learning, 2018

QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension.

Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, Quoc V. Le

Proceedings of the 6th International Conference on Learning Representations, 2018

Learning Longer-term Dependencies in RNNs with Auxiliary Losses.

Trieu H. Trinh, Andrew M. Dai, Minh-Thang Luong, Quoc V. Le

Proceedings of the 6th International Conference on Learning Representations, 2018

A Bayesian Perspective on Generalization and Stochastic Gradient Descent.

Samuel L. Smith, Quoc V. Le

Proceedings of the 6th International Conference on Learning Representations, 2018

Don't Decay the Learning Rate, Increase the Batch Size.

Samuel L. Smith, Pieter-Jan Kindermans, Chris Ying, Quoc V. Le

Proceedings of the 6th International Conference on Learning Representations, 2018

Searching for Activation Functions.

Prajit Ramachandran, Barret Zoph, Quoc V. Le

Proceedings of the 6th International Conference on Learning Representations, 2018

Can Deep Reinforcement Learning solve Erdos-Selfridge-Spencer Games?

Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc V. Le, Jon M. Kleinberg

Proceedings of the 6th International Conference on Learning Representations, 2018

Faster Discovery of Neural Architectures by Searching for Paths in a Large Model.

Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, Jeff Dean

Proceedings of the 6th International Conference on Learning Representations, 2018

A Hierarchical Model for Device Placement.

Azalia Mirhoseini, Anna Goldie, Hieu Pham, Benoit Steiner, Quoc V. Le, Jeff Dean

Proceedings of the 6th International Conference on Learning Representations, 2018

Intriguing Properties of Adversarial Examples.

Ekin Dogus Cubuk, Barret Zoph, Samuel S. Schoenholz, Quoc V. Le

Proceedings of the 6th International Conference on Learning Representations, 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

AirDialogue: An Environment for Goal-Oriented Dialogue Research.

Wei Wei, Quoc V. Le, Andrew M. Dai, Jia Li

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Semi-Supervised Sequence Modeling with Cross-View Training.

Kevin Clark, Minh-Thang Luong, Christopher D. Manning, Quoc V. Le

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Learning Transferable Architectures for Scalable Image Recognition.

Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation.

Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda B. Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, Jeffrey Dean

Trans. Assoc. Comput. Linguistics, 2017

Don't Decay the Learning Rate, Increase the Batch Size.

Samuel L. Smith, Pieter-Jan Kindermans, Quoc V. Le

CoRR, 2017

Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model.

Yuxuan Wang, R. J. Skerry-Ryan, Daisy Stanton, Yonghui Wu, Ron J. Weiss, Navdeep Jaitly, Zongheng Yang, Ying Xiao, Zhifeng Chen, Samy Bengio, Quoc V. Le, Yannis Agiomyrgiannakis, Rob Clark, Rif A. Saurous

CoRR, 2017

Large-Scale Evolution of Image Classifiers.

Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka I. Leon-Suematsu, Quoc V. Le, Alex Kurakin

CoRR, 2017

Massive Exploration of Neural Machine Translation Architectures.

Denny Britz, Anna Goldie, Minh-Thang Luong, Quoc V. Le

CoRR, 2017

Effective Domain Mixing for Neural Machine Translation.

Denny Britz, Quoc V. Le, Reid Pryzant

Proceedings of the Second Conference on Machine Translation, 2017

Tacotron: Towards End-to-End Speech Synthesis.

Yuxuan Wang, R. J. Skerry-Ryan, Daisy Stanton, Yonghui Wu, Ron J. Weiss, Navdeep Jaitly, Zongheng Yang, Ying Xiao, Zhifeng Chen, Samy Bengio, Quoc V. Le, Yannis Agiomyrgiannakis, Rob Clark, Rif A. Saurous

Proceedings of the Interspeech 2017, 2017

Large-Scale Evolution of Image Classifiers.

Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka I. Leon-Suematsu, Jie Tan, Quoc V. Le, Alexey Kurakin

Proceedings of the 34th International Conference on Machine Learning, 2017

Device Placement Optimization with Reinforcement Learning.

Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean

Proceedings of the 34th International Conference on Machine Learning, 2017

Neural Optimizer Search with Reinforcement Learning.

Irwan Bello, Barret Zoph, Vijay Vasudevan, Quoc V. Le

Proceedings of the 34th International Conference on Machine Learning, 2017

Neural Architecture Search with Reinforcement Learning.

Barret Zoph, Quoc V. Le

Proceedings of the 5th International Conference on Learning Representations, 2017

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, Jeff Dean

Proceedings of the 5th International Conference on Learning Representations, 2017

Learning a Natural Language Interface with Neural Programmer.

Arvind Neelakantan, Quoc V. Le, Martín Abadi, Andrew McCallum, Dario Amodei

Proceedings of the 5th International Conference on Learning Representations, 2017

HyperNetworks.

David Ha, Andrew M. Dai, Quoc V. Le

Proceedings of the 5th International Conference on Learning Representations, 2017

Latent Sequence Decompositions.

William Chan, Yu Zhang, Quoc V. Le, Navdeep Jaitly

Proceedings of the 5th International Conference on Learning Representations, 2017

Neural Combinatorial Optimization with Reinforcement Learning.

Irwan Bello, Hieu Pham, Quoc V. Le, Mohammad Norouzi, Samy Bengio

Proceedings of the 5th International Conference on Learning Representations, 2017

Unsupervised Pretraining for Sequence to Sequence Learning.

Prajit Ramachandran, Peter J. Liu, Quoc V. Le

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Learning to Skim Text.

Adams Wei Yu, Hongrae Lee, Quoc V. Le

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision.

Chen Liang, Jonathan Berant, Quoc V. Le, Kenneth D. Forbus, Ni Lao

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Lukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, Jeffrey Dean

CoRR, 2016

Neural Programmer: Inducing Latent Programs with Gradient Descent.

Arvind Neelakantan, Quoc V. Le, Ilya Sutskever

Proceedings of the 4th International Conference on Learning Representations, 2016

Multi-task Sequence to Sequence Learning.

Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, Oriol Vinyals, Lukasz Kaiser

Proceedings of the 4th International Conference on Learning Representations, 2016

Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision (Short Version).

Chen Liang, Jonathan Berant, Quoc V. Le, Kenneth D. Forbus, Ni Lao

CoRR, 2016

End-to-end Learning for Text and Speech.

Quoc V. Le

Proceedings of the 9th ISCA Speech Synthesis Workshop, 2016

An Online Sequence-to-Sequence Model Using Partial Conditioning.

Navdeep Jaitly, Quoc V. Le, Oriol Vinyals, Ilya Sutskever, David Sussillo, Samy Bengio

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

Listen, attend and spell: A neural network for large vocabulary conversational speech recognition.

William Chan, Navdeep Jaitly, Quoc V. Le, Oriol Vinyals

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015

A Neural Conversational Model.

Oriol Vinyals, Quoc V. Le

CoRR, 2015

Adding Gradient Noise Improves Learning for Very Deep Networks.

Arvind Neelakantan, Luke Vilnis, Quoc V. Le, Ilya Sutskever, Lukasz Kaiser, Karol Kurach, James Martens

CoRR, 2015

A Simple Way to Initialize Recurrent Networks of Rectified Linear Units.

Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton

CoRR, 2015

An Online Sequence-to-Sequence Model Using Partial Conditioning.

Navdeep Jaitly, Quoc V. Le, Oriol Vinyals, Ilya Sutskever, Samy Bengio

CoRR, 2015

Document Embedding with Paragraph Vectors.

Andrew M. Dai, Christopher Olah, Quoc V. Le

CoRR, 2015

Listen, Attend and Spell.

William Chan, Navdeep Jaitly, Quoc V. Le, Oriol Vinyals

CoRR, 2015

Semi-supervised Sequence Learning.

Andrew M. Dai, Quoc V. Le

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

Addressing the Rare Word Problem in Neural Machine Translation.

Thang Luong, Ilya Sutskever, Quoc V. Le, Oriol Vinyals, Wojciech Zaremba

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015

2014

Grounded Compositional Semantics for Finding and Describing Images with Sentences.

Richard Socher, Andrej Karpathy, Quoc V. Le, Christopher D. Manning, Andrew Y. Ng

Trans. Assoc. Comput. Linguistics, 2014

Fastfood: Approximate Kernel Expansions in Loglinear Time.

Quoc Viet Le, Tamás Sarlós, Alexander Johannes Smola

CoRR, 2014

Sequence to Sequence Learning with Neural Networks.

Ilya Sutskever, Oriol Vinyals, Quoc V. Le

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

Distributed Representations of Sentences and Documents.

Quoc V. Le, Tomás Mikolov

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

2013

Scalable feature learning.

Quoc V. Le

PhD thesis, 2013

Exploiting Similarities among Languages for Machine Translation.

Tomás Mikolov, Quoc V. Le, Ilya Sutskever

CoRR, 2013

Using Web Co-occurrence Statistics for Improving Image Categorization.

Samy Bengio, Jeffrey Dean, Dumitru Erhan, Eugene Ie, Quoc V. Le, Andrew Rabinovich, Jonathon Shlens, Yoram Singer

CoRR, 2013

Fastfood - Computing Hilbert Space Expansions in loglinear time.

Quoc V. Le, Tamás Sarlós, Alexander J. Smola

Proceedings of the 30th International Conference on Machine Learning, 2013

On rectified linear units for speech processing.

Matthew D. Zeiler, Marc'Aurelio Ranzato, Rajat Monga, Mark Z. Mao, K. Yang, Quoc Viet Le, Patrick Nguyen, Andrew W. Senior, Vincent Vanhoucke, Jeffrey Dean, Geoffrey E. Hinton

Proceedings of the IEEE International Conference on Acoustics, 2013

Building high-level features using large scale unsupervised learning.

Quoc V. Le

Proceedings of the IEEE International Conference on Acoustics, 2013

2012

Large Scale Distributed Deep Networks.

Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V. Le, Mark Z. Mao, Marc'Aurelio Ranzato, Andrew W. Senior, Paul A. Tucker, Ke Yang, Andrew Y. Ng

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

Learning invariant features of tumor signatures.

Quoc V. Le, Ju Han, Joe W. Gray, Paul T. Spellman, Alexander Borowsky, Bahram Parvin

Proceedings of the 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2012

Recurrent Neural Networks for Noise Reduction in Robust ASR.

Andrew L. Maas, Quoc V. Le, Tyler M. O'Neil, Oriol Vinyals, Patrick Nguyen, Andrew Y. Ng

Proceedings of the INTERSPEECH 2012, 2012

Building high-level features using large scale unsupervised learning.

Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Jeffrey Dean, Andrew Y. Ng

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning.

Quoc V. Le, Alexandre Karpenko, Jiquan Ngiam, Andrew Y. Ng

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

On optimization methods for deep learning.

Quoc V. Le, Jiquan Ngiam, Adam Coates, Ahbik Lahiri, Bobby Prochnow, Andrew Y. Ng

Proceedings of the 28th International Conference on Machine Learning, 2011

Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis.

Quoc V. Le, Will Y. Zou, Serena Y. Yeung, Andrew Y. Ng

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010

Bundle Methods for Regularized Risk Minimization.

Choon Hui Teo, S. V. N. Vishwanathan, Alexander J. Smola, Quoc V. Le

J. Mach. Learn. Res., 2010

Tiled convolutional neural networks.

Quoc V. Le, Jiquan Ngiam, Zhenghao Chen, Daniel Jin hao Chia, Pang Wei Koh, Andrew Y. Ng

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Grasping novel objects with depth segmentation.

Deepak Rao, Quoc V. Le, Thanathorn Phoka, Morgan Quigley, Attawith Sudsang, Andrew Y. Ng

Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

Low-cost accelerometers for robotic manipulator perception.

Morgan Quigley, Reuben D. Brewer, Sai Prashanth Soundararaj, Vijay Pradeep, Quoc V. Le, Andrew Y. Ng

Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

Learning to grasp objects with multiple contact points.

Quoc V. Le, David Kamm, Arda F. Kara, Andrew Y. Ng

Proceedings of the IEEE International Conference on Robotics and Automation, 2010

2009

Learning Graph Matching.

Tibério S. Caetano, Julian J. McAuley, Li Cheng, Quoc V. Le, Alexander J. Smola

IEEE Trans. Pattern Anal. Mach. Intell., 2009

Estimating Labels from Label Proportions.

Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, Quoc V. Le

J. Mach. Learn. Res., 2009

Measuring Invariances in Deep Networks.

Ian J. Goodfellow, Quoc V. Le, Andrew M. Saxe, Honglak Lee, Andrew Y. Ng

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Joint calibration of multiple sensors.

Quoc V. Le, Andrew Y. Ng

Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

Scalable learning for object detection with GPU hardware.

Adam Coates, Paul Baumstarck, Quoc V. Le, Andrew Y. Ng

Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

High-accuracy 3D sensing for mobile manipulation: Improving object detection and door opening.

Morgan Quigley, Siddharth Batra, Stephen Gould, Ellen Klingbeil, Quoc V. Le, Ashley Wellman, Andrew Y. Ng

Proceedings of the 2009 IEEE International Conference on Robotics and Automation, 2009

Proximal regularization for online and batch learning.

Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008

Tighter Bounds for Structured Estimation.

Olivier Chapelle, Chuong B. Do, Quoc V. Le, Alexander J. Smola, Choon Hui Teo

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007

Direct Optimization of Ranking Measures

Quoc V. Le, Alexander J. Smola

CoRR, 2007

COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking .

Markus Weimer, Alexandros Karatzoglou, Quoc V. Le, Alexander J. Smola

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Bundle Methods for Machine Learning.

Alexander J. Smola, S. V. N. Vishwanathan, Quoc V. Le

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A scalable modular convex solver for regularized risk minimization.

Choon Hui Teo, Alexander J. Smola, S. V. N. Vishwanathan, Quoc V. Le

Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Learning Graph Matching.

Tibério S. Caetano, Li Cheng, Quoc V. Le, Alexander J. Smola

Proceedings of the IEEE 11th International Conference on Computer Vision, 2007

2006

Nonparametric Quantile Estimation.

Ichiro Takeuchi, Quoc V. Le, Tim D. Sears, Alexander J. Smola

J. Mach. Learn. Res., 2006

Learning to Rank with Nonsmooth Cost Functions.

Christopher J. C. Burges, Robert Ragno, Quoc Viet Le

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Simpler knowledge-based support vector machines.

Quoc V. Le, Alexander J. Smola, Thomas Gärtner

Proceedings of the Machine Learning, 2006

Transductive Gaussian Process Regression with Automatic Model Selection.

Quoc V. Le, Alexander J. Smola, Thomas Gärtner, Yasemin Altun

Proceedings of the Machine Learning: ECML 2006, 2006

2005

Mapping Maintenance for Data Integration Systems.

Robert McCann, Bedoor K. AlShebli, Quoc Le, Hoa Nguyen, Long H. Vu, AnHai Doan

Proceedings of the 31st International Conference on Very Large Data Bases, Trondheim, Norway, August 30, 2005

Large-Scale Multiclass Transduction.

Thomas Gärtner, Quoc V. Le, Simon Burton, Alexander J. Smola, S. V. N. Vishwanathan

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Heteroscedastic Gaussian process regression.

Quoc V. Le, Alexander J. Smola, Stéphane Canu

Proceedings of the Machine Learning, 2005