Andrew G. Howard

According to our database, Andrew G. Howard authored at least 31 papers between 2004 and 2023.

Collaborative distances:

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

2023

ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation.

Shuyang Sun, Weijun Wang, Andrew G. Howard, Qihang Yu, Philip H. S. Torr, Liang-Chieh Chen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

On Label Granularity and Object Localization.

Elijah Cole, Kimberly Wilber, Grant Van Horn, Xuan Yang, Marco Fornoni, Pietro Perona, Serge J. Belongie, Andrew G. Howard, Oisin Mac Aodha

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

MOSAIC: Mobile Segmentation via decoding Aggregated Information and encoded Context.

Weijun Wang, Andrew Howard

CoRR, 2021

Bridging the Gap Between Object Detection and User Intent via Query-Modulation.

Marco Fornoni, Chaochao Yan, Liangchen Luo, Kimberly Wilber, Alex Stark, Yin Cui, Boqing Gong, Andrew G. Howard

CoRR, 2021

Multi-path Neural Networks for On-device Multi-domain Visual Classification.

Qifei Wang, Junjie Ke, Joshua Greaves, Grace Chu, Gabriel Bender, Luciano Sbaiz, Alec Go, Andrew G. Howard, Ming-Hsuan Yang, Jeff Gilbert, Peyman Milanfar, Feng Yang

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

BasisNet: Two-Stage Model Synthesis for Efficient Inference.

Mingda Zhang, Chun-Te Chu, Andrey Zhmoginov, Andrew Howard, Brendan Jou, Yukun Zhu, Li Zhang, Rebecca Hwa, Adriana Kovashka

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

Discovering Multi-Hardware Mobile Models via Architecture Search.

Grace Chu, Okan Arikan, Gabriel Bender, Weijun Wang, Achille Brighton, Pieter-Jan Kindermans, Hanxiao Liu, Berkin Akin, Suyog Gupta, Andrew Howard

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

2020

Large-Scale Generative Data-Free Distillation.

Liangchen Luo, Mark Sandler, Zi Lin, Andrey Zhmoginov, Andrew Howard

CoRR, 2020

SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection.

Keren Ye, Adriana Kovashka, Mark Sandler, Menglong Zhu, Andrew G. Howard, Marco Fornoni

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019

Low-Power Computer Vision: Status, Challenges, and Opportunities.

Sergei Alyamkin, Matthew Ardi, Alexander C. Berg, Achille Brighton, Bo Chen, Yiran Chen, Hsin-Pai Cheng, Zichen Fan, Chen Feng, Bo Fu, Kent Gauen, Abhinav Goel, Alexander Goncharenko, Xuyang Guo, Soonhoi Ha, Andrew Howard, Xiao Hu, Yuanjun Huang, Donghyun Kang, Jaeyoun Kim, Jong-gook Ko, Alexander Kondratyev, Junhyeok Lee, Seungjae Lee, Suwoong Lee, Zichao Li, Zhiyu Liang, Juzheng Liu, Xin Liu, Yang Lu, Yung-Hsiang Lu, Deeptanshu Malik, Hong Hanh Nguyen, Eunbyung Park, Denis Repin, Liang Shen, Tao Sheng, Fei Sun, David Svitov, George K. Thiruvathukal, Baiwu Zhang, Jingchi Zhang, Xiaopeng Zhang, Shaojie Zhuo

IEEE J. Emerg. Sel. Topics Circuits Syst., 2019

Visual Wake Words Dataset.

Aakanksha Chowdhery, Pete Warden, Jonathon Shlens, Andrew Howard, Rocky Rhodes

CoRR, 2019

Low-Power Computer Vision: Status, Challenges, Opportunities.

Sergei Alyamkin, Matthew Ardi, Alexander C. Berg, Achille Brighton, Bo Chen, Yiran Chen, Hsin-Pai Cheng, Zichen Fan, Chen Feng, Bo Fu, Kent Gauen, Abhinav Goel, Alexander Goncharenko, Xuyang Guo, Soonhoi Ha, Andrew Howard, Xiao Hu, Yuanjun Huang, Donghyun Kang, Jaeyoun Kim, Jong-gook Ko, Alexander Kondratyev, Junhyeok Lee, Seungjae Lee, Suwoong Lee, Zichao Li, Zhiyu Liang, Juzheng Liu, Xin Liu, Yang Lu, Yung-Hsiang Lu, Deeptanshu Malik, Hong Hanh Nguyen, Eunbyung Park, Denis Repin, Liang Shen, Tao Sheng, Fei Sun, David Svitov, George K. Thiruvathukal, Baiwu Zhang, Jingchi Zhang, Xiaopeng Zhang, Shaojie Zhuo

CoRR, 2019

K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning.

Pramod Kaushik Mudrakarta, Mark Sandler, Andrey Zhmoginov, Andrew G. Howard

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

Non-Discriminative Data or Weak Model? On the Relative Importance of Data and Model Resolution.

Mark Sandler, Jonathan Baccash, Andrey Zhmoginov, Andrew Howard

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

Geo-Aware Networks for Fine-Grained Recognition.

Grace Chu, Brian Potetz, Weijun Wang, Andrew Howard, Yang Song, Fernando Brucher, Thomas Leung, Hartwig Adam

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

2018

2018 Low-Power Image Recognition Challenge.

Sergei Alyamkin, Matthew Ardi, Achille Brighton, Alexander C. Berg, Yiran Chen, Hsin-Pai Cheng, Bo Chen, Zichen Fan, Chen Feng, Bo Fu, Kent Gauen, Jongkook Go, Alexander Goncharenko, Xuyang Guo, Hong Hanh Nguyen, Andrew Howard, Yuanjun Huang, Donghyun Kang, Jaeyoun Kim, Alexander Kondratyev, Seungjae Lee, Suwoong Lee, Junhyeok Lee, Zhiyu Liang, Xin Liu, Juzheng Liu, Zichao Li, Yang Lu, Yung-Hsiang Lu, Deeptanshu Malik, Eunbyung Park, Denis Repin, Tao Sheng, Liang Shen, Fei Sun, David Svitov, George K. Thiruvathukal, Baiwu Zhang, Jingchi Zhang, Xiaopeng Zhang, Shaojie Zhuo

CoRR, 2018

NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications.

Tien-Ju Yang, Andrew G. Howard, Bo Chen, Xiao Zhang, Alec Go, Vivienne Sze, Hartwig Adam

CoRR, 2018

Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation.

Mark Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen

CoRR, 2018

NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications.

Tien-Ju Yang, Andrew G. Howard, Bo Chen, Xiao Zhang, Alec Go, Mark Sandler, Vivienne Sze, Hartwig Adam

Proceedings of the Computer Vision - ECCV 2018, 2018

MobileNetV2: Inverted Residuals and Linear Bottlenecks.

Mark Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen

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

Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference.

Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew G. Howard, Hartwig Adam, Dmitry Kalenichenko

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

Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning.

Yin Cui, Yang Song, Chen Sun, Andrew Howard, Serge J. Belongie

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

2017

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, Hartwig Adam

CoRR, 2017

2014

Some Improvements on Deep Convolutional Neural Network Based Image Classification.

Andrew G. Howard

Proceedings of the 2nd International Conference on Learning Representations, 2014

2009

Transformation Learning Via Kernel Alignment.

Andrew G. Howard, Tony Jebara

Proceedings of the International Conference on Machine Learning and Applications, 2009

2007

Multi-object tracking with representations of the symmetric group.

Risi Kondor, Andrew G. Howard, Tony Jebara

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Learning Monotonic Transformations for Classification.

Andrew G. Howard, Tony Jebara

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

2004

Probability Product Kernels.

Tony Jebara, Risi Kondor, Andrew G. Howard

J. Mach. Learn. Res., 2004

Dynamical Systems Trees.

Andrew G. Howard, Tony Jebara

Proceedings of the UAI '04, 2004