Ning Liu

Orcid: 0000-0003-4943-6625

Affiliations:
  • Northeastern University, Boston, MA, USA
  • Syracuse University, NY, USA


According to our database1, Ning Liu authored at least 30 papers between 2016 and 2023.

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

Timeline

Legend:

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Online presence:

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Bibliography

2023
DAIS: Automatic Channel Pruning via Differentiable Annealing Indicator Search.
IEEE Trans. Neural Networks Learn. Syst., December, 2023

2022
BLCR: Towards Real-time DNN Execution with Block-based Reweighted Pruning.
Proceedings of the 23rd International Symposium on Quality Electronic Design, 2022

An Automatic and Efficient BERT Pruning for Edge AI Systems.
Proceedings of the 23rd International Symposium on Quality Electronic Design, 2022

2021
CATRO: Channel Pruning via Class-Aware Trace Ratio Optimization.
CoRR, 2021

Lottery Ticket Implies Accuracy Degradation, Is It a Desirable Phenomenon?
CoRR, 2021

MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI.
Proceedings of the 22nd International Symposium on Quality Electronic Design, 2021

Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
A Stochastic-Computing based Deep Learning Framework using Adiabatic Quantum-Flux-Parametron SuperconductingTechnology.
CoRR, 2019

AutoSlim: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates.
CoRR, 2019

Deep Compressed Pneumonia Detection for Low-Power Embedded Devices.
Proceedings of the Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention, 2019

IDE Development, Logic Synthesis and Buffer/Splitter Insertion Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits.
Proceedings of the 2019 IEEE Computer Society Annual Symposium on VLSI, 2019

A stochastic-computing based deep learning framework using adiabatic quantum-flux-parametron superconducting technology.
Proceedings of the 46th International Symposium on Computer Architecture, 2019

A Buffer and Splitter Insertion Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits.
Proceedings of the 37th IEEE International Conference on Computer Design, 2019

ADMM-based Weight Pruning for Real-Time Deep Learning Acceleration on Mobile Devices.
Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019

A Majority Logic Synthesis Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits.
Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019

REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs.
Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2019

2018
Deep reinforcement learning: Algorithm, applications, and ultra-low-power implementation.
Nano Commun. Networks, 2018

Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs.
Proceedings of the 2018 on Great Lakes Symposium on VLSI, 2018

FFT-based deep learning deployment in embedded systems.
Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018

VIBNN: Hardware Acceleration of Bayesian Neural Networks.
Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems, 2018

2017
Multisource Indoor Energy Harvesting for Nonvolatile Processors.
IEEE Des. Test, 2017

CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices.
CoRR, 2017

CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices.
Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture, 2017

Data center power management for regulation service using neural network-based power prediction.
Proceedings of the 18th International Symposium on Quality Electronic Design, 2017

Deep Reinforcement Learning for Dynamic Treatment Regimes on Medical Registry Data.
Proceedings of the 2017 IEEE International Conference on Healthcare Informatics, 2017

A Hierarchical Framework of Cloud Resource Allocation and Power Management Using Deep Reinforcement Learning.
Proceedings of the 37th IEEE International Conference on Distributed Computing Systems, 2017

2016
Neural Network-based Prediction Algorithms for In-Door Multi-Source Energy Harvesting System for Non-Volatile Processors.
Proceedings of the 26th edition on Great Lakes Symposium on VLSI, 2016


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