Quoc V. Le
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
116
Venues
17
Active years
2005–2025
Best venue rank
A*
Where they publish
Papers
116 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ACL | BIG-Bench Extra Hard. | Mehran Kazemi, Bahare Fatemi, Hritik Bansal, John Palowitch, Chrysovalantis Anastasiou, Sanket Vaibhav Mehta, Lalit K. Jain, Virginia Aglietti, Disha Jindal, Peter Chen, Nishanth Dikkala, Gladys Tyen, Xin Liu, Uri Shalit, Silvia Chiappa, Kate Olszewska, Yi Tay, Vinh Q. Tran, Quoc V. Le, Orhan Firat |
| 2025 | EMNLP | Towards Robust Mathematical Reasoning. | Thang Luong, Dawsen Hwang, Hoang H. Nguyen, Golnaz Ghiasi, Yuri Chervonyi, Insuk Seo, Junsu Kim, Garrett Bingham, Jonathan Lee, Swaroop Mishra, Alex Zhai, Clara Huiyi Hu, Henryk Michalewski, Jimin Kim, Jeonghyun Ahn, Junhwi Bae, Xingyou Song, Trieu H. Trinh, Quoc V. Le, Junehyuk Jung |
| 2025 | ICML | SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training. | Tianzhe Chu, Yuexiang Zhai, Jihan Yang, Shengbang Tong, Saining Xie, Dale Schuurmans, Quoc V. Le, Sergey Levine, Yi Ma |
| 2025 | ICML | EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration. | Allen Nie, Yi Su, Bo Chang, Jonathan Lee, Ed H. Chi, Quoc V. Le, Minmin Chen |
| 2025 | ICML | Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs. | Ziyu Ye, Rishabh Agarwal, Tianqi Liu, Rishabh Joshi, Sarmishta Velury, Quoc V. Le, Qijun Tan, Yuan Liu |
| 2024 | ACL | 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 |
| 2024 | CHI | Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses. | Xiao Ma, Swaroop Mishra, Ariel Liu, Sophie Ying Su, Jilin Chen, Chinmay Kulkarni, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi |
| 2024 | ECCV | HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning. | Zhecan Wang, Garrett Bingham, Adams Wei Yu, Quoc V. Le, Thang Luong, Golnaz Ghiasi |
| 2024 | ICLR | Large Language Models as Optimizers. | Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, Xinyun Chen |
| 2024 | ICLR | 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 |
| 2023 | ACL | Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. | Mirac Suzgun, Nathan Scales, Nathanael Schrli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed H. Chi, Denny Zhou, Jason Wei |
| 2023 | ASPLOS | 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 |
| 2023 | EMNLP | 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 |
| 2023 | EMNLP | 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 |
| 2023 | EMNLP | Inverse Scaling Can Become U-Shaped. | Jason Wei, Najoung Kim, Yi Tay, Quoc V. Le |
| 2023 | ICLR | 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 |
| 2023 | ICLR | Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. | Denny Zhou, Nathanael Schrli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi |
| 2023 | ICML | 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 |
| 2023 | ICML | 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 |
| 2022 | ASPLOS | 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 |
| 2022 | CVPR | 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 |
| 2022 | ICLR | 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 |
| 2022 | ICML | 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 |
| 2022 | ICML | Transformer Quality in Linear Time. | Weizhe Hua, Zihang Dai, Hanxiao Liu, Quoc V. Le |
| 2021 | AAAI | AutoDropout: Learning Dropout Patterns to Regularize Deep Networks. | Hieu Pham, Quoc V. Le |
| 2021 | CVPR | Searching for Fast Model Families on Datacenter Accelerators. | Sheng Li, Mingxing Tan, Ruoming Pang, Andrew Li, Liqun Cheng, Quoc V. Le, Norman P. Jouppi |
| 2021 | CVPR | 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 |
| 2021 | CVPR | Meta Pseudo Labels. | Hieu Pham, Zihang Dai, Qizhe Xie, Quoc V. Le |
| 2021 | EMNLP | STraTA: Self-Training with Task Augmentation for Better Few-shot Learning. | Tu Vu, Minh-Thang Luong, Quoc V. Le, Grady Simon, Mohit Iyyer |
| 2021 | ICCV | Multi-Task Self-Training for Learning General Representations. | Golnaz Ghiasi, Barret Zoph, Ekin D. Cubuk, Quoc V. Le, Tsung-Yi Lin |
| 2021 | ICLR | Evolving Reinforcement Learning Algorithms. | John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V. Le, Sergey Levine, Honglak Lee, Aleksandra Faust |
| 2021 | ICML | 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 |
| 2021 | ICML | EfficientNetV2: Smaller Models and Faster Training. | Mingxing Tan, Quoc V. Le |
| 2021 | ICML | Towards Domain-Agnostic Contrastive Learning. | Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc V. Le |
| 2020 | CVPR | 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 |
| 2020 | CVPR | 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 |
| 2020 | CVPR | Randaugment: Practical automated data augmentation with a reduced search space. | Ekin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le |
| 2020 | CVPR | 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 |
| 2020 | CVPR | EfficientDet: Scalable and Efficient Object Detection. | Mingxing Tan, Ruoming Pang, Quoc V. Le |
| 2020 | CVPR | Self-Training With Noisy Student Improves ImageNet Classification. | Qizhe Xie, Minh-Thang Luong, Eduard H. Hovy, Quoc V. Le |
| 2020 | CVPR | Adversarial Examples Improve Image Recognition. | Cihang Xie, Mingxing Tan, Boqing Gong, Jiang Wang, Alan L. Yuille, Quoc V. Le |
| 2020 | ECCV | 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 |
| 2020 | ECCV | Efficient Scale-Permuted Backbone with Learned Resource Distribution. | Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Yin Cui, Mingxing Tan, Quoc V. Le, Xiaodan Song |
| 2020 | ECCV | Learning Data Augmentation Strategies for Object Detection. | Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le |
| 2020 | EMNLP | Pre-Training Transformers as Energy-Based Cloze Models. | Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning |
| 2020 | ICASSP | Specaugment on Large Scale Datasets. | Daniel S. Park, Yu Zhang, Chung-Cheng Chiu, Youzheng Chen, Bo Li, William Chan, Quoc V. Le, Yonghui Wu |
| 2020 | ICLR | 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 |
| 2020 | ICLR | ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators. | Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning |
| 2020 | ICML | AutoML-Zero: Evolving Machine Learning Algorithms From Scratch. | Esteban Real, Chen Liang, David R. So, Quoc V. Le |
| 2020 | ICML | 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 |
| 2020 | Interspeech | 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 |
| 2020 | KDD | 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 |
| 2019 | AAAI | Regularized Evolution for Image Classifier Architecture Search. | Esteban Real, Alok Aggarwal, Yanping Huang, Quoc V. Le |
| 2019 | ACL | BAM! Born-Again Multi-Task Networks for Natural Language Understanding. | Kevin Clark, Minh-Thang Luong, Urvashi Khandelwal, Christopher D. Manning, Quoc V. Le |
| 2019 | BMVC | MixConv: Mixed Depthwise Convolutional Kernels. | Mingxing Tan, Quoc V. Le |
| 2019 | CVPR | AutoAugment: Learning Augmentation Strategies From Data. | Ekin D. Cubuk, Barret Zoph, Dandelion Man, Vijay Vasudevan, Quoc V. Le |
| 2019 | CVPR | NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection. | Golnaz Ghiasi, Tsung-Yi Lin, Quoc V. Le |
| 2019 | CVPR | Do Better ImageNet Models Transfer Better? | Simon Kornblith, Jonathon Shlens, Quoc V. Le |
| 2019 | CVPR | MnasNet: Platform-Aware Neural Architecture Search for Mobile. | Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, Quoc V. Le |
| 2019 | ICCV | 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 |
| 2019 | ICLR | Diversity and Depth in Per-Example Routing Models. | Prajit Ramachandran, Quoc V. Le |
| 2019 | ICML | 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 |
| 2019 | ICML | The Evolved Transformer. | David R. So, Quoc V. Le, Chen Liang |
| 2019 | ICML | EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. | Mingxing Tan, Quoc V. Le |
| 2019 | Interspeech | 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 |
| 2018 | CVPR | Learning Transferable Architectures for Scalable Image Recognition. | Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le |
| 2018 | EMNLP | Semi-Supervised Sequence Modeling with Cross-View Training. | Kevin Clark, Minh-Thang Luong, Christopher D. Manning, Quoc V. Le |
| 2018 | EMNLP | AirDialogue: An Environment for Goal-Oriented Dialogue Research. | Wei Wei, Quoc V. Le, Andrew M. Dai, Jia Li |
| 2018 | GECCO | Evolving modular neural sequence architectures with genetic programming. | David Dohan, David R. So, Quoc V. Le |
| 2018 | ICLR | Intriguing Properties of Adversarial Examples. | Ekin Dogus Cubuk, Barret Zoph, Samuel S. Schoenholz, Quoc V. Le |
| 2018 | ICLR | A Hierarchical Model for Device Placement. | Azalia Mirhoseini, Anna Goldie, Hieu Pham, Benoit Steiner, Quoc V. Le, Jeff Dean |
| 2018 | ICLR | 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 |
| 2018 | ICLR | Can Deep Reinforcement Learning solve Erdos-Selfridge-Spencer Games? | Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc V. Le, Jon M. Kleinberg |
| 2018 | ICLR | Searching for Activation Functions. | Prajit Ramachandran, Barret Zoph, Quoc V. Le |
| 2018 | ICLR | Don't Decay the Learning Rate, Increase the Batch Size. | Samuel L. Smith, Pieter-Jan Kindermans, Chris Ying, Quoc V. Le |
| 2018 | ICLR | A Bayesian Perspective on Generalization and Stochastic Gradient Descent. | Samuel L. Smith, Quoc V. Le |
| 2018 | ICLR | Learning Longer-term Dependencies in RNNs with Auxiliary Losses. | Trieu H. Trinh, Andrew M. Dai, Minh-Thang Luong, Quoc V. Le |
| 2018 | ICLR | 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 |
| 2018 | ICML | Understanding and Simplifying One-Shot Architecture Search. | Gabriel Bender, Pieter-Jan Kindermans, Barret Zoph, Vijay Vasudevan, Quoc V. Le |
| 2018 | ICML | Efficient Neural Architecture Search via Parameter Sharing. | Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, Jeff Dean |
| 2018 | ICML | Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games? | Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc V. Le, Jon M. Kleinberg |
| 2018 | ICML | Learning Longer-term Dependencies in RNNs with Auxiliary Losses. | Trieu H. Trinh, Andrew M. Dai, Thang Luong, Quoc V. Le |
| 2017 | ACL | Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision. | Chen Liang, Jonathan Berant, Quoc V. Le, Kenneth D. Forbus, Ni Lao |
| 2017 | ACL | Learning to Skim Text. | Adams Wei Yu, Hongrae Lee, Quoc V. Le |
| 2017 | EMNLP | Unsupervised Pretraining for Sequence to Sequence Learning. | Prajit Ramachandran, Peter J. Liu, Quoc V. Le |
| 2017 | ICLR | Neural Combinatorial Optimization with Reinforcement Learning. | Irwan Bello, Hieu Pham, Quoc V. Le, Mohammad Norouzi, Samy Bengio |
| 2017 | ICLR | Latent Sequence Decompositions. | William Chan, Yu Zhang, Quoc V. Le, Navdeep Jaitly |
| 2017 | ICLR | HyperNetworks. | David Ha, Andrew M. Dai, Quoc V. Le |
| 2017 | ICLR | Learning a Natural Language Interface with Neural Programmer. | Arvind Neelakantan, Quoc V. Le, Martn Abadi, Andrew McCallum, Dario Amodei |
| 2017 | ICLR | 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 |
| 2017 | ICLR | Neural Architecture Search with Reinforcement Learning. | Barret Zoph, Quoc V. Le |
| 2017 | ICML | Neural Optimizer Search with Reinforcement Learning. | Irwan Bello, Barret Zoph, Vijay Vasudevan, Quoc V. Le |
| 2017 | ICML | 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 |
| 2017 | ICML | 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 |
| 2017 | Interspeech | 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 |
| 2016 | ICASSP | Listen, attend and spell: A neural network for large vocabulary conversational speech recognition. | William Chan, Navdeep Jaitly, Quoc V. Le, Oriol Vinyals |
| 2015 | ACL | Addressing the Rare Word Problem in Neural Machine Translation. | Thang Luong, Ilya Sutskever, Quoc V. Le, Oriol Vinyals, Wojciech Zaremba |
| 2014 | ICML | Distributed Representations of Sentences and Documents. | Quoc V. Le, Toms Mikolov |
| 2013 | ICASSP | Building high-level features using large scale unsupervised learning. | Quoc V. Le |
| 2013 | ICML | Fastfood - Computing Hilbert Space Expansions in loglinear time. | Quoc V. Le, Tams Sarls, Alexander J. Smola |
| 2012 | ICML | 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 |
| 2012 | Interspeech | 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 |
| 2011 | CVPR | 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 |
| 2011 | ICML | On optimization methods for deep learning. | Quoc V. Le, Jiquan Ngiam, Adam Coates, Ahbik Lahiri, Bobby Prochnow, Andrew Y. Ng |
| 2010 | ICRA | Learning to grasp objects with multiple contact points. | Quoc V. Le, David Kamm, Arda F. Kara, Andrew Y. Ng |
| 2010 | IROS | Low-cost accelerometers for robotic manipulator perception. | Morgan Quigley, Reuben D. Brewer, Sai Prashanth Soundararaj, Vijay Pradeep, Quoc V. Le, Andrew Y. Ng |
| 2010 | IROS | Grasping novel objects with depth segmentation. | Deepak Rao, Quoc V. Le, Thanathorn Phoka, Morgan Quigley, Attawith Sudsang, Andrew Y. Ng |
| 2009 | ICML | Proximal regularization for online and batch learning. | Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo |
| 2009 | ICRA | 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 |
| 2009 | IROS | Scalable learning for object detection with GPU hardware. | Adam Coates, Paul Baumstarck, Quoc V. Le, Andrew Y. Ng |
| 2009 | IROS | Joint calibration of multiple sensors. | Quoc V. Le, Andrew Y. Ng |
| 2008 | ICML | Estimating labels from label proportions. | Novi Quadrianto, Alexander J. Smola, Tibrio S. Caetano, Quoc V. Le |
| 2007 | ICCV | Learning Graph Matching. | Tibrio S. Caetano, Li Cheng, Quoc V. Le, Alexander J. Smola |
| 2007 | KDD | A scalable modular convex solver for regularized risk minimization. | Choon Hui Teo, Alexander J. Smola, S. V. N. Vishwanathan, Quoc V. Le |
| 2006 | ICML | Simpler knowledge-based support vector machines. | Quoc V. Le, Alexander J. Smola, Thomas Grtner |
| 2005 | ICML | Heteroscedastic Gaussian process regression. | Quoc V. Le, Alexander J. Smola, Stphane Canu |