Zhuo Wang

Orcid: 0000-0002-3296-8599

Affiliations:
  • Princeton University, Department of Electrical Engineering, NJ, USA


According to our database1, Zhuo Wang authored at least 17 papers between 2013 and 2017.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2017
A Low-Energy Machine-Learning Classifier Based on Clocked Comparators for Direct Inference on Analog Sensors.
IEEE Trans. Circuits Syst. I Regul. Pap., 2017

In-Memory Computation of a Machine-Learning Classifier in a Standard 6T SRAM Array.
IEEE J. Solid State Circuits, 2017

2016
Reducing Quantization Errors for Inner-Product Operations in Embedded Digital Signal Processing Systems [Tips&Tricks].
IEEE Signal Process. Mag., 2016

A Large-Area Image Sensing and Detection System Based on Embedded Thin-Film Classifiers.
IEEE J. Solid State Circuits, 2016

A machine-learning classifier implemented in a standard 6T SRAM array.
Proceedings of the 2016 IEEE Symposium on VLSI Circuits, 2016

2015
Hardware Specialization in Low-power Sensing Applications to Address Energy and Resilience.
J. Signal Process. Syst., 2015

Overcoming Computational Errors in Sensing Platforms Through Embedded Machine-Learning Kernels.
IEEE Trans. Very Large Scale Integr. Syst., 2015

Error Adaptive Classifier Boosting (EACB): Leveraging Data-Driven Training Towards Hardware Resilience for Signal Inference.
IEEE Trans. Circuits Syst. I Regul. Pap., 2015

Realizing Low-Energy Classification Systems by Implementing Matrix Multiplication Directly Within an ADC.
IEEE Trans. Biomed. Circuits Syst., 2015

18.4 A matrix-multiplying ADC implementing a machine-learning classifier directly with data conversion.
Proceedings of the 2015 IEEE International Solid-State Circuits Conference, 2015

16.2 A large-area image sensing and detection system based on embedded thin-film classifiers.
Proceedings of the 2015 IEEE International Solid-State Circuits Conference, 2015

Reducing quantization error in low-energy FIR filter accelerators.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

A seizure-detection IC employing machine learning to overcome data-conversion and analog-processing non-idealities.
Proceedings of the 2015 IEEE Custom Integrated Circuits Conference, 2015

A look at signal analysis in resource-constrained medical-sensor applications.
Proceedings of the IEEE Biomedical Circuits and Systems Conference, 2015

2014
Error-adaptive classifier boosting (EACB): Exploiting data-driven training for highly fault-tolerant hardware.
Proceedings of the IEEE International Conference on Acoustics, 2014

Enabling hardware relaxations through statistical learning.
Proceedings of the 52nd Annual Allerton Conference on Communication, 2014

2013
Hardware specialization of machine-learning kernels: Possibilities for applications and possibilities for the platform design space (Invited).
Proceedings of the IEEE Workshop on Signal Processing Systems, 2013


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