Dynamical Systems Trees. - Andrew G. Howard; Tony Jebara (UAI, 2004)

Probability Product Kernels. - Tony Jebara; Risi Kondor; Andrew G. Howard (J. Mach. Learn. Res., 2004)

Learning Monotonic Transformations for Classification. - Andrew G. Howard; Tony Jebara (NIPS, 2007)

Multi-object tracking with representations of the symmetric group. - Risi Kondor; Andrew G. Howard; Tony Jebara (AISTATS, 2007)

Transformation Learning Via Kernel Alignment. - Andrew G. Howard; Tony Jebara (ICMLA, 2009)

Some Improvements on Deep Convolutional Neural Network Based Image Classification. - Andrew G. Howard (ICLR (Poster), 2014)

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. - Andrew G. Howard; Menglong Zhu; Bo Chen 019; Dmitry Kalenichenko; Weijun Wang; Tobias Weyand; Marco Andreetto; Hartwig Adam (CoRR, 2017)

Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning. - Yin Cui; Yang Song 009; Chen Sun 002; Andrew Howard 002; Serge J. Belongie (CVPR, 2018)

Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference. - Benoit Jacob; Skirmantas Kligys; Bo Chen 019; Menglong Zhu; Matthew Tang; Andrew G. Howard; Hartwig Adam; Dmitry Kalenichenko (CVPR, 2018)

MobileNetV2: Inverted Residuals and Linear Bottlenecks. - Mark Sandler 002; Andrew G. Howard; Menglong Zhu; Andrey Zhmoginov; Liang-Chieh Chen (CVPR, 2018)

NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications. - Tien-Ju Yang; Andrew G. Howard; Bo Chen 019; Xiao Zhang; Alec Go; Mark Sandler 002; Vivienne Sze; Hartwig Adam (ECCV (10), 2018)

Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation. - Mark Sandler 002; 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 019; Xiao Zhang; Alec Go; Vivienne Sze; Hartwig Adam (CoRR, 2018)

2018 Low-Power Image Recognition Challenge. - Sergei Alyamkin; Matthew Ardi; Achille Brighton; Alexander C. Berg; Yiran Chen 001; Hsin-Pai Cheng; Bo Chen 019; Zichen Fan; Chen Feng; Bo Fu; Kent Gauen; Jongkook Go; et al. (CoRR, 2018)

MnasNet: Platform-Aware Neural Architecture Search for Mobile. - Mingxing Tan; Bo Chen 019; Ruoming Pang; Vijay Vasudevan; Mark Sandler 002; Andrew Howard 002; Quoc V. Le (CVPR, 2019)

Searching for MobileNetV3. - Andrew Howard 002; Ruoming Pang; Hartwig Adam; Quoc V. Le; Mark Sandler 002; Bo Chen 019; Weijun Wang; Liang-Chieh Chen; Mingxing Tan; Grace Chu; Vijay Vasudevan; Yukun Zhu (ICCV, 2019)

Geo-Aware Networks for Fine-Grained Recognition. - Grace Chu; Brian Potetz; Weijun Wang; Andrew Howard 002; Yang Song 009; Fernando Brucher; Thomas Leung; Hartwig Adam (ICCV Workshops, 2019)

Non-Discriminative Data or Weak Model? On the Relative Importance of Data and Model Resolution. - Mark Sandler 002; Jonathan Baccash; Andrey Zhmoginov; Andrew Howard 002 (ICCV Workshops, 2019)

K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning. - Pramod Kaushik Mudrakarta; Mark Sandler 002; Andrey Zhmoginov; Andrew G. Howard (ICLR (Poster), 2019)

Low-Power Computer Vision: Status, Challenges, Opportunities. - Sergei Alyamkin; Matthew Ardi; Alexander C. Berg; Achille Brighton; Bo Chen 019; Yiran Chen 001; Hsin-Pai Cheng; Zichen Fan; Chen Feng; Bo Fu; Kent Gauen; Abhinav Goel; et al. (CoRR, 2019)

Visual Wake Words Dataset. - Aakanksha Chowdhery; Pete Warden; Jonathon Shlens; Andrew Howard 002; Rocky Rhodes (CoRR, 2019)

Low-Power Computer Vision: Status, Challenges, and Opportunities. - Sergei Alyamkin; Matthew Ardi; Alexander C. Berg; Achille Brighton; Bo Chen 019; Yiran Chen 001; Hsin-Pai Cheng; Zichen Fan; Chen Feng; Bo Fu; Kent Gauen; Abhinav Goel; et al. (IEEE J. Emerg. Sel. Topics Circuits Syst., 2019)

SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection. - Keren Ye; Adriana Kovashka; Mark Sandler 002; Menglong Zhu; Andrew G. Howard; Marco Fornoni (ECCV Workshops (1), 2020)

Large-Scale Generative Data-Free Distillation. - Liangchen Luo; Mark Sandler 002; Zi Lin; Andrey Zhmoginov; Andrew Howard 002 (CoRR, 2020)

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 002 (CVPR Workshops, 2021)

BasisNet: Two-Stage Model Synthesis for Efficient Inference. - Mingda Zhang; Chun-Te Chu; Andrey Zhmoginov; Andrew Howard 002; Brendan Jou; Yukun Zhu; Li Zhang 003; Rebecca Hwa; Adriana Kovashka (CVPR Workshops, 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 001; Jeff Gilbert; Peyman Milanfar; Feng Yang 008 (WACV, 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)

MOSAIC: Mobile Segmentation via decoding Aggregated Information and encoded Context. - Weijun Wang; Andrew Howard 002 (CoRR, 2021)

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 (ECCV (10), 2022)

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 (NeurIPS, 2023)

PikeLPN: Mitigating Overlooked Inefficiencies of Low-Precision Neural Networks. - Marina Neseem; Conor McCullough; Randy Hsin; Chas Leichner; Shan Li 001; In Suk Chong; Andrew G. Howard; Lukasz Lew; Sherief Reda; Ville-Mikko Rautio; Daniele Moro (CVPR, 2024)

MobileNetV4: Universal Models for the Mobile Ecosystem. - Danfeng Qin; Chas Leichner; Manolis Delakis; Marco Fornoni; Shixin Luo; Fan Yang; Weijun Wang; Colby R. Banbury; Chengxi Ye; Berkin Akin; Vaibhav Aggarwal; Tenghui Zhu; et al. (ECCV (40), 2024)

Custom Gradient Estimators are Straight-Through Estimators in Disguise. - Matt Schoenbauer; Daniele Moro; Lukasz Lew; Andrew Howard 002 (CoRR, 2024)

Robust Training of Neural Networks at Arbitrary Precision and Sparsity. - Chengxi Ye; Grace Chu; Yanfeng Liu; Yichi Zhang; Lukasz Lew; Andrew G. Howard (CoRR, 2024)