Chuteng Zhou

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 18

Top Topics

Transfer Learning

Processing Units

Top Venues

Publications

Bokun Wang, Axel Berg, Durmus Alp Emre Acar, Chuteng Zhou
Towards Federated Learning with On-device Training and Communication in 8-bit Floating Point. CoRR (2024)
Abhishek Tyagi, Reiley Jeyapaul, Chuteng Zhou, Paul N. Whatmough, Yuhao Zhu
Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator. ISPASS (2024)
Yuji Chai, Devashree Tripathy, Chuteng Zhou, Dibakar Gope, Igor Fedorov, Ramon Matas Navarro, David Brooks, Gu-Yeon Wei, Paul N. Whatmough
PerfSAGE: Generalized Inference Performance Predictor for Arbitrary Deep Learning Models on Edge Devices. CoRR (2023)
Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough
UDC: Unified DNAS for Compressible TinyML Models for Neural Processing Units. NeurIPS (2022)
Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough
UDC: Unified DNAS for Compressible TinyML Models. CoRR (2022)
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
ML-HW Co-Design of Noise-Robust TinyML Models and Always-On Analog Compute-in-Memory Edge Accelerator. IEEE Micro 42 (6) (2022)
Chuteng Zhou, Quntao Zhuang, Matthew Mattina, Paul N. Whatmough
Strong data processing inequality in neural networks with noisy neurons and its implications. ISIT (2021)
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
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator. CoRR (2021)
Gregory W. Gundersen, Diana Cai, Chuteng Zhou, Barbara E. Engelhardt, Ryan P. Adams
Active multi-fidelity Bayesian online changepoint detection. UAI (2021)
Gregory W. Gundersen, Diana Cai, Chuteng Zhou, Barbara E. Engelhardt, Ryan P. Adams
Active multi-fidelity Bayesian online changepoint detection. CoRR (2021)
Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers. MLSys (2021)
Chuteng Zhou, Quntao Zhuang, Matthew Mattina, Paul N. Whatmough
Information contraction in noisy binary neural networks and its implications. CoRR (2021)
Jian Meng, Shreyas Kolala Venkataramanaiah, Chuteng Zhou, Patrick Hansen, Paul N. Whatmough, Jae-sun Seo
FixyFPGA: Efficient FPGA Accelerator for Deep Neural Networks with High Element-Wise Sparsity and without External Memory Access. FPL (2021)
Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers. CoRR (2020)
Chuteng Zhou, Prad Kadambi, Matthew Mattina, Paul N. Whatmough
Noisy Machines: Understanding Noisy Neural Networks and Enhancing Robustness to Analog Hardware Errors Using Distillation. CoRR (2020)
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas K. Venkataramanaiah, Jae-sun Seo, Matthew Mattina
FixyNN: Energy-Efficient Real-Time Mobile Computer Vision Hardware Acceleration via Transfer Learning. MLSys (2019)
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas K. Venkataramanaiah, Jae-sun Seo, Matthew Mattina
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning. CoRR (2019)
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Matthew Mattina
Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning. CoRR (2018)