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2020 – today
- 2023
[i22]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)- [i21]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 abs/2305.08298 (2023) - [i20]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 abs/2305.09617 (2023) - 2022
- [c11]Le Hou, Richard Yuanzhe Pang, Tianyi Zhou, Yuexin Wu, Xinying Song, Xiaodan Song, Denny Zhou:
Token Dropping for Efficient BERT Pretraining. ACL (1) 2022: 3774-3784 - [i19]Le Hou, Richard Yuanzhe Pang, Tianyi Zhou, Yuexin Wu, Xinying Song, Xiaodan Song, Denny Zhou:
Token Dropping for Efficient BERT Pretraining. CoRR abs/2203.13240 (2022) - [i18]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) - [i17]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) - [i16]Jiaxin Huang, Shixiang Shane Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han:
Large Language Models Can Self-Improve. CoRR abs/2210.11610 (2022) - [i15]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 abs/2210.11768 (2022) - 2021
- [j2]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): 1337-1351 (2021) - [i14]Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, Denny Zhou:
Speeding up Deep Model Training by Sharing Weights and Then Unsharing. CoRR abs/2110.03848 (2021) - 2020
- [c10]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: 481-485 - [i13]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 abs/2002.07913 (2020) - [i12]Noam Shazeer, Zhenzhong Lan, Youlong Cheng, Nan Ding, Le Hou:
Talking-Heads Attention. CoRR abs/2003.02436 (2020)
2010 – 2019
- 2019
- [j1]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: 188-200 (2019) - [c9]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: 1488-1496 - [c8]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: 371-379 - [c7]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: 8533-8542 - [c6]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: 12726-12735 - [c5]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 - [i11]Maozheng Zhao, Le Hou, Han Le, Dimitris Samaras, Nebojsa Jojic, Danielle Fassler, Tahsin M. Kurç, Rajarsi R. Gupta, Kolya Malkin, Shahira Abousamra, Kenneth Shroyer, Joel H. Saltz:
Label Super Resolution with Inter-Instance Loss. CoRR abs/1904.04429 (2019) - [i10]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 abs/1905.10841 (2019) - [i9]Shahira Abousamra, Le Hou, Rajarsi R. Gupta, Chao Chen, Dimitris Samaras, Tahsin M. Kurç, Rebecca Batiste, Tianhao Zhao, Kenneth Shroyer, Joel H. Saltz:
Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types. CoRR abs/1907.03960 (2019) - [i8]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 abs/1909.03108 (2019) - [i7]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 abs/1909.12291 (2019) - 2017
- [c4]Le Hou, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, Joel H. Saltz:
ConvNets with Smooth Adaptive Activation Functions for Regression. AISTATS 2017: 430-439 - [c3]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: 834-841 - [i6]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 abs/1704.00406 (2017) - [i5]Le Hou, Ayush Agarwal, Dimitris Samaras, Tahsin M. Kurç, Rajarsi R. Gupta, Joel H. Saltz:
Unsupervised Histopathology Image Synthesis. CoRR abs/1712.05021 (2017) - 2016
- [c2]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: 2424-2433 - [c1]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: 816-832 - [i4]Le Hou, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, Joel H. Saltz:
Neural Networks with Smooth Adaptive Activation Functions for Regression. CoRR abs/1608.06557 (2016) - [i3]Le Hou, Chen-Ping Yu, Dimitris Samaras:
Squared Earth Mover's Distance-based Loss for Training Deep Neural Networks. CoRR abs/1611.05916 (2016) - [i2]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 abs/1612.06825 (2016) - 2015
- [i1]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 abs/1504.07947 (2015)
Coauthor Index
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last updated on 2023-05-25 22:25 CEST by the dblp team
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