Le Hou

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 53

Top Topics

Histopathology Images

Activation Function

Convolutional Neural Networks

Top Venues

Publications

Ziqi Wang, Le Hou, Tianjian Lu, Yuexin Wu, Yunxuan Li, Hongkun Yu, Heng Ji
Enabling Lanuguage Models to Implicitly Learn Self-Improvement. ICLR (2024)
Tao Tu, Anil Palepu, Mike Schaekermann, Khaled Saab, Jan Freyberg, Ryutaro Tanno, Amy Wang, Brenna Li, Mohamed Amin, Nenad Tomasev, Shekoofeh Azizi, Karan Singhal, Yong Cheng, Le Hou, Albert Webson, Kavita Kulkarni, S. Sara Mahdavi, Christopher Semturs, Juraj Gottweis, Joelle K. Barral, Katherine Chou, Gregory S. Corrado, Yossi Matias, Alan Karthikesalingam, Vivek Natarajan
Towards Conversational Diagnostic AI. CoRR (2024)
Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, Juanma Zambrano Chaves, Szu-Yeu Hu, Mike Schaekermann, Aishwarya Kamath, Yong Cheng, David G. T. Barrett, Cathy Cheung, Basil Mustafa, Anil Palepu, Daniel McDuff, Le Hou, Tomer Golany, Luyang Liu, Jean-Baptiste Alayrac, Neil Houlsby, Nenad Tomasev, Jan Freyberg, Charles Lau, Jonas Kemp, Jeremy Lai, Shekoofeh Azizi, Kimberly Kanada, SiWai Man, Kavita Kulkarni, Ruoxi Sun, Siamak Shakeri, Luheng He, Benjamin Caine, Albert Webson, Natasha Latysheva, Melvin Johnson, Philip Andrew Mansfield, Jian Lu, Ehud Rivlin, Jesper Anderson, Bradley Green, Renee Wong, Jonathan Krause, Jonathon Shlens, Ewa Dominowska, S. M. Ali Eslami, Katherine Chou, Claire Cui, Oriol Vinyals, Koray Kavukcuoglu, James Manyika, Jeff Dean, Demis Hassabis, Yossi Matias, Dale R. Webster, Joelle K. Barral, Greg Corrado, Christopher Semturs, S. Sara Mahdavi, Juraj Gottweis, Alan Karthikesalingam, Vivek Natarajan
Capabilities of Gemini Models in Medicine. CoRR (2024)
Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Y. Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, Denny Zhou
Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models. ICLR (2024)
Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Avinava Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent
Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning. CoRR (2024)
Yunxuan Li, Yibing Du, Jiageng Zhang, Le Hou, Peter Grabowski, Yeqing Li, Eugene Ie
Improving Multi-Agent Debate with Sparse Communication Topology. CoRR (2024)
Zihan Wang, Yunxuan Li, Yuexin Wu, Liangchen Luo, Le Hou, Hongkun Yu, Jingbo Shang
Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process Supervision. CoRR (2024)
Chiyu Zhang, Honglong Cai, Yuezhang Li, Yuexin Wu, Le Hou, Muhammad Abdul-Mageed
Distilling Text Style Transfer With Self-Explanation From LLMs. CoRR (2024)
Huaixiu Steven Zheng, Swaroop Mishra, Hugh Zhang, Xinyun Chen, Minmin Chen, Azade Nova, Le Hou, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou
NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. CoRR (2024)
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. EMNLP (2023)
Ziqi Wang, Le Hou, Tianjian Lu, Yuexin Wu, Yunxuan Li, Hongkun Yu, Heng Ji
Enable Language Models to Implicitly Learn Self-Improvement From Data. CoRR (2023)
Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, Siddhartha Brahma, Sujoy Basu, Yi Luan, Denny Zhou, Le Hou
Instruction-Following Evaluation for Large Language Models. CoRR (2023)
Jiaxin Huang, Shixiang Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han
Large Language Models Can Self-Improve. EMNLP (2023)
Ziqi Wang, Yuexin Wu, Frederick Liu, Daogao Liu, Le Hou, Hongkun Yu, Jing Li, Heng Ji
Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation. ICLR (2023)
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. ICML (2023)
Jerry W. Wei, Le Hou, Andrew 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 (2023)
Daniel McDuff, Mike Schaekermann, Tao Tu, Anil Palepu, Amy Wang, Jake Garrison, Karan Singhal, Yash Sharma, Shekoofeh Azizi, Kavita Kulkarni, Le Hou, Yong Cheng, Yun Liu, S. Sara Mahdavi, Sushant Prakash, Anupam Pathak, Christopher Semturs, Shwetak N. Patel, Dale R. Webster, Ewa Dominowska, Juraj Gottweis, Joelle K. Barral, Katherine Chou, Gregory S. Corrado, Yossi Matias, Jake Sunshine, Alan Karthikesalingam, Vivek Natarajan
Towards Accurate Differential Diagnosis with Large Language Models. CoRR (2023)
Vu Nguyen, Prantik Howlader, Le Hou, Dimitris Samaras, Rajarsi R. Gupta, Joel H. Saltz
Few Shot Hematopoietic Cell Classification. MIDL (2023)
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. ICLR (2023)
Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, Denny Zhou
Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts. CoRR (2023)
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 (2023)
Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Le Hou, Kevin Clark, Stephen Pfohl, Heather Cole-Lewis, Darlene Neal, Mike Schaekermann, Amy Wang, Mohamed Amin, Sami Lachgar, Philip Andrew Mansfield, Sushant Prakash, Bradley Green, Ewa Dominowska, Blaise Agüera y Arcas, Nenad Tomasev, Yun Liu, Renee Wong, Christopher Semturs, S. Sara Mahdavi, Joelle K. Barral, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Shekoofeh Azizi, Alan Karthikesalingam, Vivek Natarajan
Towards Expert-Level Medical Question Answering with Large Language Models. CoRR (2023)
Le Hou, Richard Yuanzhe Pang, Tianyi Zhou, Yuexin Wu, Xinying Song, Xiaodan Song, Denny Zhou
Token Dropping for Efficient BERT Pretraining. ACL (1) (2022)
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 (2022)
Le Hou, Richard Yuanzhe Pang, Tianyi Zhou, Yuexin Wu, Xinying Song, Xiaodan Song, Denny Zhou
Token Dropping for Efficient BERT Pretraining. CoRR (2022)
Jiaxin Huang, Shixiang Shane Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han
Large Language Models Can Self-Improve. CoRR (2022)
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 (2022)
Ziqi Wang, Yuexin Wu, Frederick Liu, Daogao Liu, Le Hou, Hongkun Yu, Jing Li, Heng Ji
Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation. CoRR (2022)
Le Hou, Tomás F. Yago Vicente, Minh Hoai, Dimitris Samaras
Large Scale Shadow Annotation and Detection Using Lazy Annotation and Stacked CNNs. IEEE Trans. Pattern Anal. Mach. Intell. 43 (4) (2021)
Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, Denny Zhou
Speeding up Deep Model Training by Sharing Weights and Then Unsharing. CoRR (2021)
Le Hou, Rajarsi Gupta, John S. Van Arnam, Yuwei Zhang, Kaustubh Sivalenka, Dimitris Samaras, Tahsin M. Kurç, Joel H. Saltz
Dataset of Segmented Nuclei in Hematoxylin and Eosin Stained Histopathology Images of 10 Cancer Types. CoRR (2020)
Noam Shazeer, Zhenzhong Lan, Youlong Cheng, Nan Ding, Le Hou
Talking-Heads Attention. CoRR (2020)
Shahira Abousamra, Danielle Fassler, Le Hou, Yuwei Zhang, Rajarsi Gupta, Tahsin M. Kurç, Luisa F. Escobar-Hoyos, Dimitris Samaras, Beatrice Knudson, Kenneth Shroyer, Joel H. Saltz, Chao Chen
Weakly-Supervised Deep Stain Decomposition for Multiplex IHC Images. ISBI (2020)
Le Hou, Youlong Cheng, Noam Shazeer, Niki Parmar, Yeqing Li, Panagiotis Korfiatis, Travis M. Drucker, Daniel J. Blezek, Xiaodan Song
High Resolution Medical Image Analysis with Spatial Partitioning. CoRR (2019)
Han Le, Rajarsi R. Gupta, Le Hou, Shahira Abousamra, Danielle Fassler, Tahsin M. Kurç, Dimitris Samaras, Rebecca Batiste, Tianhao Zhao, Alison L. Van Dyke, Ashish Sharma, Erich Bremer, Jonas S. Almeida, Joel H. Saltz
Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor Infiltrating Lymphocytes in Invasive Breast Cancer. CoRR (2019)
Caleb Robinson, Le Hou, Kolya Malkin, Rachel Soobitsky, Jacob Czawlytko, Bistra Dilkina, Nebojsa Jojic
Large Scale High-Resolution Land Cover Mapping With Multi-Resolution Data. CVPR (2019)
Robert M. Patton, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou
Exascale Deep Learning to Accelerate Cancer Research. IEEE BigData (2019)
Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz
Exascale Deep Learning to Accelerate Cancer Research. CoRR (2019)
Maozheng Zhao, Le Hou, Han Le, Dimitris Samaras, Nebojsa Jojic, Danielle Fassler, Tahsin M. Kurç, Rajarsi R. Gupta, Kolya Malkin, Shahira Abousamra, Shroyer Kenneth, Joel H. Saltz
Label Super Resolution with Inter-Instance Loss. CoRR (2019)
Tahsin M. Kurç, Ashish Sharma, Rajarsi Gupta, Le Hou, Han Le, Shahira Abousamra, Erich Bremer, Ryan Birmingham, Tammy Diprima, Nan Li, Feiqiao Wang, Joseph Balsamo, Whitney Bremer, Dimitris Samaras, Joel H. Saltz
From Whole Slide Tissues to Knowledge: Mapping Sub-cellular Morphology of Cancer. BrainLes@MICCAI (2) (2019)
Kolya Malkin, Caleb Robinson, Le Hou, Rachel Soobitsky, Jacob Czawlytko, Dimitris Samaras, Joel H. Saltz, Lucas Joppa, Nebojsa Jojic
Label super-resolution networks. ICLR (Poster) (2019)
Le Hou, Vu Nguyen, Ariel B. Kanevsky, Dimitris Samaras, Tahsin M. Kurç, Tianhao Zhao, Rajarsi R. Gupta, Yi Gao, Wenjin Chen, David J. Foran, Joel H. Saltz
Sparse autoencoder for unsupervised nucleus detection and representation in histopathology images. Pattern Recognit. 86 (2019)
Le Hou, Ayush Agarwal, Dimitris Samaras, Tahsin M. Kurç, Rajarsi R. Gupta, Joel H. Saltz
Robust Histopathology Image Analysis: To Label or to Synthesize? CVPR (2019)
Shahira Abousamra, Le Hou, Rajarsi R. Gupta, Chao Chen, Dimitris Samaras, Tahsin M. Kurç, Rebecca Batiste, Tianhao Zhao, Shroyer Kenneth, Joel H. Saltz
Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types. CoRR (2019)
Le Hou, Ayush Agarwal, Dimitris Samaras, Tahsin M. Kurç, Rajarsi R. Gupta, Joel H. Saltz
Unsupervised Histopathology Image Synthesis. CoRR (2017)
Le Hou, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, Joel H. Saltz
ConvNets with Smooth Adaptive Activation Functions for Regression. AISTATS (2017)
Veda Murthy, Le Hou, Dimitris Samaras, Tahsin M. Kurç, Joel H. Saltz
Center-Focusing Multi-task CNN with Injected Features for Classification of Glioma Nuclear Images. WACV (2017)
Le Hou, Vu Nguyen, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, Tianhao Zhao, Joel H. Saltz
Sparse Autoencoder for Unsupervised Nucleus Detection and Representation in Histopathology Images. CoRR (2017)
Le Hou, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, Joel H. Saltz
Neural Networks with Smooth Adaptive Activation Functions for Regression. CoRR (2016)
Le Hou, Chen-Ping Yu, Dimitris Samaras
Squared Earth Mover's Distance-based Loss for Training Deep Neural Networks. CoRR (2016)
Le Hou, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, James E. Davis, Joel H. Saltz
Patch-Based Convolutional Neural Network for Whole Slide Tissue Image Classification. CVPR (2016)
Tomás F. Yago Vicente, Le Hou, Chen-Ping Yu, Minh Hoai, Dimitris Samaras
Large-Scale Training of Shadow Detectors with Noisily-Annotated Shadow Examples. ECCV (6) (2016)
Veda Murthy, Le Hou, Dimitris Samaras, Tahsin M. Kurç, Joel H. Saltz
Center-Focusing Multi-task CNN with Injected Features for Classification of Glioma Nuclear Images. CoRR (2016)
Le Hou, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, James E. Davis, Joel H. Saltz
Efficient Multiple Instance Convolutional Neural Networks for Gigapixel Resolution Image Classification. CoRR (2015)