Andrew G. Howard

29 papers A* 4A 3C 1Journal 13Unranked 8

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	MobileNetV4: Universal Models for the Mobile Ecosystem. ECCV (40) 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, Daniele Moro, Andrew G. Howard
2024	A*	`conf`	PikeLPN: Mitigating Overlooked Inefficiencies of Low-Precision Neural Networks. CVPR 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
2024	J	`jnl`	PikeLPN: Mitigating Overlooked Inefficiencies of Low-Precision Neural Networks. CoRR 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
2024	J	`jnl`	Robust Training of Neural Networks at Arbitrary Precision and Sparsity. CoRR Chengxi Ye, Grace Chu, Yanfeng Liu, Yichi Zhang, Lukasz Lew, Andrew G. Howard
2023	A*	`conf`	ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation. NeurIPS Shuyang Sun, Weijun Wang, Andrew G. Howard, Qihang Yu, Philip H. S. Torr, Liang-Chieh Chen
2023	J	`jnl`	ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation. CoRR Shuyang Sun, Weijun Wang, Qihang Yu, Andrew G. Howard, Philip H. S. Torr, Liang-Chieh Chen
2022	—	`conf`	On Label Granularity and Object Localization. ECCV (10) Elijah Cole, Kimberly Wilber, Grant Van Horn, Xuan Yang, Marco Fornoni, Pietro Perona, Serge J. Belongie, Andrew G. Howard, Oisin Mac Aodha
2022	J	`jnl`	On Label Granularity and Object Localization. CoRR Elijah Cole, Kimberly Wilber, Grant Van Horn, Xuan Yang, Marco Fornoni, Pietro Perona, Serge J. Belongie, Andrew G. Howard, Oisin Mac Aodha
2021	J	`jnl`	BasisNet: Two-stage Model Synthesis for Efficient Inference. CoRR Mingda Zhang, Chun-Te Chu, Andrey Zhmoginov, Andrew G. Howard, Brendan Jou, Yukun Zhu, Li Zhang, Rebecca Hwa, Adriana Kovashka
2021	J	`jnl`	Bridging the Gap Between Object Detection and User Intent via Query-Modulation. CoRR Marco Fornoni, Chaochao Yan, Liangchen Luo, Kimberly Wilber, Alex Stark, Yin Cui, Boqing Gong, Andrew G. Howard
2021	A	`conf`	Multi-path Neural Networks for On-device Multi-domain Visual Classification. WACV 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
2020	—	`conf`	SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection. ACCV (6) Keren Ye, Adriana Kovashka, Mark Sandler, Menglong Zhu, Andrew G. Howard, Marco Fornoni
2020	—	`conf`	SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection. ECCV Workshops (1) Keren Ye, Adriana Kovashka, Mark Sandler, Menglong Zhu, Andrew G. Howard, Marco Fornoni
2019	—	`conf`	K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning. ICLR (Poster) Pramod Kaushik Mudrakarta, Mark Sandler, Andrey Zhmoginov, Andrew G. Howard
2018	J	`jnl`	Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation. CoRR Mark Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen
2018	J	`jnl`	K For The Price Of 1: Parameter Efficient Multi-task And Transfer Learning. CoRR Pramod Kaushik Mudrakarta, Mark Sandler, Andrey Zhmoginov, Andrew G. Howard
2018	A*	`conf`	MobileNetV2: Inverted Residuals and Linear Bottlenecks. CVPR Mark Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen
2018	—	`conf`	NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications. ECCV (10) Tien-Ju Yang, Andrew G. Howard, Bo Chen, Xiao Zhang, Alec Go, Mark Sandler, Vivienne Sze, Hartwig Adam
2018	J	`jnl`	NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications. CoRR Tien-Ju Yang, Andrew G. Howard, Bo Chen, Xiao Zhang, Alec Go, Vivienne Sze, Hartwig Adam
2018	A*	`conf`	Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference. CVPR Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew G. Howard, Hartwig Adam, Dmitry Kalenichenko
2017	J	`jnl`	MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. CoRR Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, Hartwig Adam
2017	J	`jnl`	Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference. CoRR Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew G. Howard, Hartwig Adam, Dmitry Kalenichenko
2014	—	`conf`	Some Improvements on Deep Convolutional Neural Network Based Image Classification. ICLR (Poster) Andrew G. Howard
2012	J	`jnl`	Dynamical Systems Trees CoRR Andrew G. Howard, Tony Jebara
2009	C	`conf`	Transformation Learning Via Kernel Alignment. ICMLA Andrew G. Howard, Tony Jebara
2007	—	`conf`	Learning Monotonic Transformations for Classification. NIPS Andrew G. Howard, Tony Jebara
2007	A	`conf`	Multi-object tracking with representations of the symmetric group. AISTATS Risi Kondor, Andrew G. Howard, Tony Jebara
2004	A	`conf`	Dynamical Systems Trees. UAI Andrew G. Howard, Tony Jebara
2004	J	`jnl`	Probability Product Kernels. J. Mach. Learn. Res. Tony Jebara, Risi Kondor, Andrew G. Howard