Chuteng Zhou

20 papers A* 1A 1B 3C 1Journal 12Unranked 2
YearRankTypeTitle / Venue / Authors
2024 B conf
Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator.
ISPASS
Abhishek Tyagi, Reiley Jeyapaul, Chuteng Zhou, Paul N. Whatmough, Yuhao Zhu
2024 J jnl
Towards Federated Learning with On-device Training and Communication in 8-bit Floating Point.
CoRR
Bokun Wang, Axel Berg, Durmus Alp Emre Acar, Chuteng Zhou
2024 C conf
wav2pos: Sound Source Localization using Masked Autoencoders.
IPIN
Axel Berg, Jens Gulin, Mark O'Connor, Chuteng Zhou, Karl Åström, Magnus Oskarsson
2024 J jnl
wav2pos: Sound Source Localization using Masked Autoencoders.
CoRR
Axel Berg, Jens Gulin, Mark O'Connor, Chuteng Zhou, Kalle Åström, Magnus Oskarsson
2023 J jnl
PerfSAGE: Generalized Inference Performance Predictor for Arbitrary Deep Learning Models on Edge Devices.
CoRR
Yuji Chai, Devashree Tripathy, Chuteng Zhou, Dibakar Gope, Igor Fedorov, Ramon Matas Navarro, David Brooks, Gu-Yeon Wei, Paul N. Whatmough
2022 J jnl
ML-HW Co-Design of Noise-Robust TinyML Models and Always-On Analog Compute-in-Memory Edge Accelerator.
IEEE Micro
Chuteng Zhou, Fernando García-Redondo, Julian Büchel, Irem Boybat, Xavier Timoneda Comas, S. R. Nandakumar, Shidhartha Das, Abu Sebastian, Manuel Le Gallo, Paul N. Whatmough
2022 A* conf
UDC: Unified DNAS for Compressible TinyML Models for Neural Processing Units.
NeurIPS
Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough
2022 J jnl
UDC: Unified DNAS for Compressible TinyML Models.
CoRR
Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough
2021 A conf
Active multi-fidelity Bayesian online changepoint detection.
UAI
Gregory W. Gundersen, Diana Cai, Chuteng Zhou, Barbara E. Engelhardt, Ryan P. Adams
2021 J jnl
Active multi-fidelity Bayesian online changepoint detection.
CoRR
Gregory W. Gundersen, Diana Cai, Chuteng Zhou, Barbara E. Engelhardt, Ryan P. Adams
2021 J jnl
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator.
CoRR
Chuteng Zhou, Fernando García-Redondo, Julian Büchel, Irem Boybat, Xavier Timoneda Comas, S. R. Nandakumar, Shidhartha Das, Abu Sebastian, Manuel Le Gallo, Paul N. Whatmough
2021 B conf
FixyFPGA: Efficient FPGA Accelerator for Deep Neural Networks with High Element-Wise Sparsity and without External Memory Access.
FPL
Jian Meng, Shreyas Kolala Venkataramanaiah, Chuteng Zhou, Patrick Hansen, Paul N. Whatmough, Jae-sun Seo
2021 J jnl
Information contraction in noisy binary neural networks and its implications.
CoRR
Chuteng Zhou, Quntao Zhuang, Matthew Mattina, Paul N. Whatmough
2021 — conf
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers.
MLSys
Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
2021 B conf
Strong data processing inequality in neural networks with noisy neurons and its implications.
ISIT
Chuteng Zhou, Quntao Zhuang, Matthew Mattina, Paul N. Whatmough
2020 J jnl
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers.
CoRR
Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
2020 J jnl
Noisy Machines: Understanding Noisy Neural Networks and Enhancing Robustness to Analog Hardware Errors Using Distillation.
CoRR
Chuteng Zhou, Prad Kadambi, Matthew Mattina, Paul N. Whatmough
2019 J jnl
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning.
CoRR
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas K. Venkataramanaiah, Jae-sun Seo, Matthew Mattina
2019 — conf
FixyNN: Energy-Efficient Real-Time Mobile Computer Vision Hardware Acceleration via Transfer Learning.
SysML
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas K. Venkataramanaiah, Jae-sun Seo, Matthew Mattina
2018 J jnl
Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning.
CoRR
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Matthew Mattina