Andrew G. Howard

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 19

Top Topics

Transfer Learning

Mobile Applications

Integer Arithmetic

Top Venues

Publications

Marina Neseem, Conor McCullough, Randy Hsin, Chas Leichner, Shan Li, In Suk Chong, Andrew G. Howard, Lukasz Lew, Sherief Reda, Ville-Mikko Rautio, Daniele Moro
PikeLPN: Mitigating Overlooked Inefficiencies of Low-Precision Neural Networks. CoRR (2024)
Shuyang Sun, Weijun Wang, Andrew G. Howard, Qihang Yu, Philip H. S. Torr, Liang-Chieh Chen
ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation. NeurIPS (2023)
Shuyang Sun, Weijun Wang, Qihang Yu, Andrew G. Howard, Philip H. S. Torr, Liang-Chieh Chen
ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation. CoRR (2023)
Elijah Cole, Kimberly Wilber, Grant Van Horn, Xuan Yang, Marco Fornoni, Pietro Perona, Serge J. Belongie, Andrew G. Howard, Oisin Mac Aodha
On Label Granularity and Object Localization. CoRR (2022)
Elijah Cole, Kimberly Wilber, Grant Van Horn, Xuan Yang, Marco Fornoni, Pietro Perona, Serge J. Belongie, Andrew G. Howard, Oisin Mac Aodha
On Label Granularity and Object Localization. ECCV (10) (2022)
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
Multi-path Neural Networks for On-device Multi-domain Visual Classification. WACV (2021)
Mingda Zhang, Chun-Te Chu, Andrey Zhmoginov, Andrew G. Howard, Brendan Jou, Yukun Zhu, Li Zhang, Rebecca Hwa, Adriana Kovashka
BasisNet: Two-stage Model Synthesis for Efficient Inference. CoRR (2021)
Marco Fornoni, Chaochao Yan, Liangchen Luo, Kimberly Wilber, Alex Stark, Yin Cui, Boqing Gong, Andrew G. Howard
Bridging the Gap Between Object Detection and User Intent via Query-Modulation. CoRR (2021)
Keren Ye, Adriana Kovashka, Mark Sandler, Menglong Zhu, Andrew G. Howard, Marco Fornoni
SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection. ECCV Workshops (1) (2020)
Keren Ye, Adriana Kovashka, Mark Sandler, Menglong Zhu, Andrew G. Howard, Marco Fornoni
SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection. ACCV (6) (2020)
Pramod Kaushik Mudrakarta, Mark Sandler, Andrey Zhmoginov, Andrew G. Howard
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning. ICLR (Poster) (2019)
Tien-Ju Yang, Andrew G. Howard, Bo Chen, Xiao Zhang, Alec Go, Vivienne Sze, Hartwig Adam
NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications. CoRR (2018)
Tien-Ju Yang, Andrew G. Howard, Bo Chen, Xiao Zhang, Alec Go, Mark Sandler, Vivienne Sze, Hartwig Adam
NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications. ECCV (10) (2018)
Mark Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen
MobileNetV2: Inverted Residuals and Linear Bottlenecks. CVPR (2018)
Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew G. Howard, Hartwig Adam, Dmitry Kalenichenko
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference. CVPR (2018)
Mark Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen
Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation. CoRR (2018)
Pramod Kaushik Mudrakarta, Mark Sandler, Andrey Zhmoginov, Andrew G. Howard
K For The Price Of 1: Parameter Efficient Multi-task And Transfer Learning. CoRR (2018)
Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, Hartwig Adam
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. CoRR (2017)
Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew G. Howard, Hartwig Adam, Dmitry Kalenichenko
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference. CoRR (2017)
Andrew G. Howard
Some Improvements on Deep Convolutional Neural Network Based Image Classification. ICLR (Poster) (2014)
Andrew G. Howard, Tony Jebara
Dynamical Systems Trees CoRR (2012)
Andrew G. Howard, Tony Jebara
Transformation Learning Via Kernel Alignment. ICMLA (2009)
Andrew G. Howard, Tony Jebara
Learning Monotonic Transformations for Classification. NIPS (2007)
Risi Kondor, Andrew G. Howard, Tony Jebara
Multi-object tracking with representations of the symmetric group. AISTATS (2007)
Tony Jebara, Risi Kondor, Andrew G. Howard
Probability Product Kernels. J. Mach. Learn. Res. 5 (2004)
Andrew G. Howard, Tony Jebara
Dynamical Systems Trees. UAI (2004)