Mingxing Tan

According to our database, Mingxing Tan authored at least 57 papers between 2010 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting.

Kan Chen, Runzhou Ge, Hang Qiu, Rami Ai-Rfou, Charles R. Qi, Xuanyu Zhou, Zoey Yang, Scott Ettinger, Pei Sun, Zhaoqi Leng, Mustafa Mustafa, Ivan Bogun, Weiyue Wang, Mingxing Tan, Dragomir Anguelov

CoRR, 2023

LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection.

Tong He, Pei Sun, Zhaoqi Leng, Chenxi Liu, Dragomir Anguelov, Mingxing Tan

IROS, 2023

Lidar Augment: Searching for Scalable 3D LiDAR Data Augmentations.

Zhaoqi Leng, Guowang Li, Chenxi Liu, Ekin Dogus Cubuk, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan

Proceedings of the IEEE International Conference on Robotics and Automation, 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

2022

Occupancy Flow Fields for Motion Forecasting in Autonomous Driving.

Reza Mahjourian, Jinkyu Kim, Yuning Chai, Mingxing Tan, Ben Sapp, Dragomir Anguelov

IEEE Robotics Autom. Lett., 2022

LidarAugment: Searching for Scalable 3D LiDAR Data Augmentations.

Zhaoqi Leng, Guowang Li, Chenxi Liu, Ekin Dogus Cubuk, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan

CoRR, 2022

PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions.

Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Xiaojie Shi, Shuyang Cheng, Dragomir Anguelov

CoRR, 2022

Revisiting Multi-Scale Feature Fusion for Semantic Segmentation.

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

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

Towards the Co-design of Neural Networks and Accelerators.

Yanqi Zhou, Xuanyi Dong, Tianjian Meng, Mingxing Tan, Berkin Akin, Daiyi Peng, Amir Yazdanbakhsh, Da Huang, Ravi Narayanaswami, James Laudon

Proceedings of Machine Learning and Systems 2022, 2022

PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions.

Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Jay Shi, Shuyang Cheng, Dragomir Anguelov

Proceedings of the Tenth International Conference on Learning Representations, 2022

SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds.

Pei Sun, Mingxing Tan, Weiyue Wang, Chenxi Liu, Fei Xia, Zhaoqi Leng, Dragomir Anguelov

Proceedings of the Computer Vision - ECCV 2022, 2022

LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds.

Chenxi Liu, Zhaoqi Leng, Pei Sun, Shuyang Cheng, Charles R. Qi, Yin Zhou, Mingxing Tan, Dragomir Anguelov

Proceedings of the Computer Vision - ECCV 2022, 2022

PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds.

Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov

Proceedings of the Computer Vision - ECCV 2022, 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

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

Rethinking Co-design of Neural Architectures and Hardware Accelerators.

Yanqi Zhou, Xuanyi Dong, Berkin Akin, Mingxing Tan, Daiyi Peng, Tianjian Meng, Amir Yazdanbakhsh, Da Huang, Ravi Narayanaswami, James Laudon

CoRR, 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

EfficientNetV2: Smaller Models and Faster Training.

Mingxing Tan, Quoc V. Le

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

Shape-Texture Debiased Neural Network Training.

Yingwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan L. Yuille, Cihang Xie

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

MobileDets: Searching for Object Detection Architectures for Mobile Accelerators.

Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Yongzhe Wang, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen

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

MoViNets: Mobile Video Networks for Efficient Video Recognition.

Dan Kondratyuk, Liangzhe Yuan, Yandong Li, Li Zhang, Mingxing Tan, Matthew Brown, Boqing Gong

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

Robust and Accurate Object Detection via Adversarial Learning.

Xiangning Chen, Cihang Xie, Mingxing Tan, Li Zhang, Cho-Jui Hsieh, Boqing Gong

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

Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention.

Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh

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

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

When Ensembling Smaller Models is More Efficient than Single Large Models.

Dan Kondratyuk, Mingxing Tan, Matthew Brown, Boqing Gong

CoRR, 2020

MobileDets: Searching for Object Detection Architectures for Mobile Accelerators.

Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen

CoRR, 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

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

AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures.

Michael S. Ryoo, A. J. Piergiovanni, Mingxing Tan, Anelia Angelova

Proceedings of the 8th International Conference on Learning Representations, 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

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

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

Search to Distill: Pearls Are Everywhere but Not the Eyes.

Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang

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

2019

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

Mingxing Tan, Quoc V. Le

Proceedings of the 36th International Conference on Machine Learning, 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

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

MixConv: Mixed Depthwise Convolutional Kernels.

Mingxing Tan, Quoc V. Le

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

2018

MnasNet: Platform-Aware Neural Architecture Search for Mobile.

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

CoRR, 2018

2017

Architecture and Synthesis for Area-Efficient Pipelining of Irregular Loop Nests.

Gai Liu, Mingxing Tan, Steve Dai, Ritchie Zhao, Zhiru Zhang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2017

2015

An Energy-Efficient Branch Prediction with Grouped Global History.

Mingkai Huang, Dan He, Xianhua Liu, Mingxing Tan, Xu Cheng

Proceedings of the 44th International Conference on Parallel Processing, 2015

ElasticFlow: A Complexity-Effective Approach for Pipelining Irregular Loop Nests.

Mingxing Tan, Gai Liu, Ritchie Zhao, Steve Dai, Zhiru Zhang

Proceedings of the IEEE/ACM International Conference on Computer-Aided Design, 2015

Mapping-Aware Constrained Scheduling for LUT-Based FPGAs.

Mingxing Tan, Steve Dai, Udit Gupta, Zhiru Zhang

Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2015

Area-efficient pipelining for FPGA-targeted high-level synthesis.

Ritchie Zhao, Mingxing Tan, Steve Dai, Zhiru Zhang

Proceedings of the 52nd Annual Design Automation Conference, 2015

2014

Architectural Specialization for Inter-Iteration Loop Dependence Patterns.

Shreesha Srinath, Berkin Ilbeyi, Mingxing Tan, Gai Liu, Zhiru Zhang, Christopher Batten

Proceedings of the 47th Annual IEEE/ACM International Symposium on Microarchitecture, 2014

CASA: correlation-aware speculative adders.

Gai Liu, Ye Tao, Mingxing Tan, Zhiru Zhang

Proceedings of the International Symposium on Low Power Electronics and Design, 2014

Multithreaded pipeline synthesis for data-parallel kernels.

Mingxing Tan, Bin Liu, Steve Dai, Zhiru Zhang

Proceedings of the IEEE/ACM International Conference on Computer-Aided Design, 2014

Flushing-Enabled Loop Pipelining for High-Level Synthesis.

Steve Dai, Mingxing Tan, Kecheng Hao, Zhiru Zhang

Proceedings of the 51st Annual Design Automation Conference 2014, 2014

2012

CVP: an energy-efficient indirect branch prediction with compiler-guided value pattern.

Mingxing Tan, Xianhua Liu, Tong Tong, Xu Cheng

Proceedings of the International Conference on Supercomputing, 2012

Energy-efficient branch prediction with Compiler-guided History Stack.

Mingxing Tan, Xianhua Liu, Zichao Xie, Dong Tong, Xu Cheng

Proceedings of the 2012 Design, Automation & Test in Europe Conference & Exhibition, 2012

2010

Bit-level optimization for high-level synthesis and FPGA-based acceleration.

Jiyu Zhang, Zhiru Zhang, Sheng Zhou, Mingxing Tan, Xianhua Liu, Xu Cheng, Jason Cong

Proceedings of the ACM/SIGDA 18th International Symposium on Field Programmable Gate Arrays, 2010