Ning Liu

According to our database, Ning Liu authored at least 43 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

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

Wenzheng Hu, Zhengping Che, Ning Liu, Mingyang Li, Jian Tang, Changshui Zhang, Jianqiang Wang

IEEE Trans. Neural Networks Learn. Syst., August, 2024

Discrete Policy: Learning Disentangled Action Space for Multi-Task Robotic Manipulation.

Kun Wu, Yichen Zhu, Jinming Li, Junjie Wen, Ning Liu, Zhiyuan Xu, Qinru Qiu, Jian Tang

CoRR, 2024

Scaling Diffusion Policy in Transformer to 1 Billion Parameters for Robotic Manipulation.

Minjie Zhu, Yichen Zhu, Jinming Li, Junjie Wen, Zhiyuan Xu, Ning Liu, Ran Cheng, Chaomin Shen, Yaxin Peng, Feifei Feng, Jian Tang

CoRR, 2024

TinyVLA: Towards Fast, Data-Efficient Vision-Language-Action Models for Robotic Manipulation.

Junjie Wen, Yichen Zhu, Jinming Li, Minjie Zhu, Kun Wu, Zhiyuan Xu, Ning Liu, Ran Cheng, Chaomin Shen, Yaxin Peng, Feifei Feng, Jian Tang

CoRR, 2024

MMRo: Are Multimodal LLMs Eligible as the Brain for In-Home Robotics?

Jinming Li, Yichen Zhu, Zhiyuan Xu, Jindong Gu, Minjie Zhu, Xin Liu, Ning Liu, Yaxin Peng, Feifei Feng, Jian Tang

CoRR, 2024

Mipha: A Comprehensive Overhaul of Multimodal Assistant with Small Language Models.

Minjie Zhu, Yichen Zhu, Xin Liu, Ning Liu, Zhiyuan Xu, Chaomin Shen, Yaxin Peng, Zhicai Ou, Feifei Feng, Jian Tang

CoRR, 2024

A Survey on Robotics with Foundation Models: toward Embodied AI.

Zhiyuan Xu, Kun Wu, Junjie Wen, Jinming Li, Ning Liu, Zhengping Che, Jian Tang

CoRR, 2024

SWBT: Similarity Weighted Behavior Transformer with the Imperfect Demonstration for Robotic Manipulation.

Kun Wu, Ning Liu, Zhen Zhao, Di Qiu, Jinming Li, Zhengping Che, Zhiyuan Xu, Qinru Qiu, Jian Tang

CoRR, 2024

LLaVA-Phi: Efficient Multi-Modal Assistant with Small Language Model.

Yichen Zhu, Minjie Zhu, Ning Liu, Zhicai Ou, Xiaofeng Mou, Jian Tang

CoRR, 2024

EPSD: Early Pruning with Self-Distillation for Efficient Model Compression.

Dong Chen, Ning Liu, Yichen Zhu, Zhengping Che, Rui Ma, Fachao Zhang, Xiaofeng Mou, Yi Chang, Jian Tang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

DAIS: Automatic Channel Pruning via Differentiable Annealing Indicator Search.

Yushuo Guan, Ning Liu, Pengyu Zhao, Zhengping Che, Kaigui Bian, Yanzhi Wang, Jian Tang

IEEE Trans. Neural Networks Learn. Syst., December, 2023

CMG-Net: An End-to-End Contact-based Multi-Finger Dexterous Grasping Network.

Mingze Wei, Yaomin Huang, Zhiyuan Xu, Ning Liu, Zhengping Che, Xinyu Zhang, Chaomin Shen, Feifei Feng, Chun Shan, Jian Tang

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

ScaleKD: Distilling Scale-Aware Knowledge in Small Object Detector.

Yichen Zhu, Qiqi Zhou, Ning Liu, Zhiyuan Xu, Zhicai Ou, Xiaofeng Mou, Jian Tang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

CP³: Channel Pruning Plug-in for Point-Based Networks.

Yaomin Huang, Ning Liu, Zhengping Che, Zhiyuan Xu, Chaomin Shen, Yaxin Peng, Guixu Zhang, Xinmei Liu, Feifei Feng, Jian Tang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Teach Less, Learn More: On the Undistillable Classes in Knowledge Distillation.

Yichen Zhu, Ning Liu, Zhiyuan Xu, Xin Liu, Weibin Meng, Louis Wang, Zhicai Ou, Jian Tang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

BLCR: Towards Real-time DNN Execution with Block-based Reweighted Pruning.

Xiaolong Ma, Geng Yuan, Zhengang Li, Yifan Gong, Tianyun Zhang, Wei Niu, Zheng Zhan, Pu Zhao, Ning Liu, Jian Tang, Xue Lin, Bin Ren, Yanzhi Wang

Proceedings of the 23rd International Symposium on Quality Electronic Design, 2022

An Automatic and Efficient BERT Pruning for Edge AI Systems.

Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding

Proceedings of the 23rd International Symposium on Quality Electronic Design, 2022

2021

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

Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang

CoRR, 2021

MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge.

Geng Yuan, Xiaolong Ma, Wei Niu, Zhengang Li, Zhenglun Kong, Ning Liu, Yifan Gong, Zheng Zhan, Chaoyang He, Qing Jin, Siyue Wang, Minghai Qin, Bin Ren, Yanzhi Wang, Sijia Liu, Xue Lin

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?

Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang

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.

Geng Yuan, Zhiheng Liao, Xiaolong Ma, Yuxuan Cai, Zhenglun Kong, Xuan Shen, Jingyan Fu, Zhengang Li, Chengming Zhang, Hongwu Peng, Ning Liu, Ao Ren, Jinhui Wang, Yanzhi Wang

Proceedings of the 22nd International Symposium on Quality Electronic Design, 2021

Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?

Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates.

Ning Liu, Xiaolong Ma, Zhiyuan Xu, Yanzhi Wang, Jian Tang, Jieping Ye

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.

Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Nobuyuki Yoshikawa, Yanzhi Wang

CoRR, 2019

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

Ning Liu, Xiaolong Ma, Zhiyuan Xu, Yanzhi Wang, Jian Tang, Jieping Ye

CoRR, 2019

Deep Compressed Pneumonia Detection for Low-Power Embedded Devices.

Hongjia Li, Sheng Lin, Ning Liu, Caiwen Ding, Yanzhi Wang

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.

Ruizhe Cai, Xiaolong Ma, Olivia Chen, Ao Ren, Ning Liu, Nobuyuki Yoshikawa, Yanzhi Wang

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.

Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Nobuyuki Yoshikawa, Yanzhi Wang

Proceedings of the 46th International Symposium on Computer Architecture, 2019

A Buffer and Splitter Insertion Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits.

Ruizhe Cai, Olivia Chen, Ao Ren, Ning Liu, Nobuyuki Yoshikawa, Yanzhi Wang

Proceedings of the 37th IEEE International Conference on Computer Design, 2019

ADMM-based Weight Pruning for Real-Time Deep Learning Acceleration on Mobile Devices.

Hongjia Li, Ning Liu, Xiaolong Ma, Sheng Lin, Shaokai Ye, Tianyun Zhang, Xue Lin, Wenyao Xu, Yanzhi Wang

Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019

A Majority Logic Synthesis Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits.

Ruizhe Cai, Olivia Chen, Ao Ren, Ning Liu, Caiwen Ding, Nobuyuki Yoshikawa, Yanzhi Wang

Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019

REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs.

Caiwen Ding, Shuo Wang, Ning Liu, Kaidi Xu, Yanzhi Wang, Yun Liang

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.

Hongjia Li, Ruizhe Cai, Ning Liu, Xue Lin, Yanzhi Wang

Nano Commun. Networks, 2018

Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs.

Caiwen Ding, Ao Ren, Geng Yuan, Xiaolong Ma, Jiayu Li, Ning Liu, Bo Yuan, Yanzhi Wang

Proceedings of the 2018 on Great Lakes Symposium on VLSI, 2018

FFT-based deep learning deployment in embedded systems.

Sheng Lin, Ning Liu, Mahdi Nazemi, Hongjia Li, Caiwen Ding, Yanzhi Wang, Massoud Pedram

Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018

VIBNN: Hardware Acceleration of Bayesian Neural Networks.

Ruizhe Cai, Ao Ren, Ning Liu, Caiwen Ding, Luhao Wang, Xuehai Qian, Massoud Pedram, Yanzhi Wang

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.

Caiwen Ding, Ning Liu, Yanzhi Wang, Ji Li, Soroush Heidari, Jingtong Hu, Yongpan Liu

IEEE Des. Test, 2017

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

Caiwen Ding, Siyu Liao, Yanzhi Wang, Zhe Li, Ning Liu, Youwei Zhuo, Chao Wang, Xuehai Qian, Yu Bai, Geng Yuan, Xiaolong Ma, Yipeng Zhang, Jian Tang, Qinru Qiu, Xue Lin, Bo Yuan

CoRR, 2017

CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices.

Caiwen Ding, Siyu Liao, Yanzhi Wang, Zhe Li, Ning Liu, Youwei Zhuo, Chao Wang, Xuehai Qian, Yu Bai, Geng Yuan, Xiaolong Ma, Yipeng Zhang, Jian Tang, Qinru Qiu, Xue Lin, Bo Yuan

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.

Ning Liu, Xue Lin, Yanzhi Wang

Proceedings of the 18th International Symposium on Quality Electronic Design, 2017

Deep Reinforcement Learning for Dynamic Treatment Regimes on Medical Registry Data.

Ying Liu, Brent Logan, Ning Liu, Zhiyuan Xu, Jian Tang, Yanzhi Wang

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.

Ning Liu, Zhe Li, Jielong Xu, Zhiyuan Xu, Sheng Lin, Qinru Qiu, Jian Tang, Yanzhi Wang

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.

Ning Liu, Caiwen Ding, Yanzhi Wang, Jingtong Hu

Proceedings of the 26th edition on Great Lakes Symposium on VLSI, 2016