Li Yang

Orcid: 0000-0002-2839-6196

Affiliations:
  • University of North Carolina at Charlotte, NC, USA
  • Arizona State University, Tempe, AZ, USA (Ph.D.)


According to our database1, Li Yang authored at least 41 papers between 2018 and 2024.

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Bibliography

2024
A Progressive Subnetwork Searching Framework for Dynamic Inference.
IEEE Trans. Neural Networks Learn. Syst., March, 2024

LP-3DGS: Learning to Prune 3D Gaussian Splatting.
CoRR, 2024

Hyb-Learn: A Framework for On-Device Self-Supervised Continual Learning with Hybrid RRAM/SRAM Memory.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

EMGAN: Early-Mix-GAN on Extracting Server-Side Model in Split Federated Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
MF-NeRF: Memory Efficient NeRF with Mixed-Feature Hash Table.
CoRR, 2023

Model Extraction Attacks on Split Federated Learning.
CoRR, 2023

Efficient Self-supervised Continual Learning with Progressive Task-correlated Layer Freezing.
CoRR, 2023

Slimmed Asymmetrical Contrastive Learning and Cross Distillation for Lightweight Model Training.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Hybrid RRAM/SRAM in-Memory Computing for Robust DNN Acceleration.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

Exploring Model Stability of Deep Neural Networks for Reliable RRAM-Based In-Memory Acceleration.
IEEE Trans. Computers, 2022

Temperature-Resilient RRAM-Based In-Memory Computing for DNN Inference.
IEEE Micro, 2022

Get More at Once: Alternating Sparse Training with Gradient Correction.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Beyond Not-Forgetting: Continual Learning with Backward Knowledge Transfer.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sparse and Robust RRAM-based Efficient In-memory Computing for DNN Inference.
Proceedings of the IEEE International Reliability Physics Symposium, 2022

TRGP: Trust Region Gradient Projection for Continual Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

XST: A Crossbar Column-wise Sparse Training for Efficient Continual Learning.
Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

XMA: a crossbar-aware multi-task adaption framework via shift-based mask learning method.
Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

RepNet: Efficient On-Device Learning via Feature Reprogramming.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

DA<sup>3</sup>: Dynamic Additive Attention Adaption for Memory-Efficient On-Device Multi-Domain Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Contrastive Dual Gating: Learning Sparse Features With Contrastive Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

XBM: A Crossbar Column-wise Binary Mask Learning Method for Efficient Multiple Task Adaption.
Proceedings of the 27th Asia and South Pacific Design Automation Conference, 2022

Efficient Multi-task Adaption for Crossbar-based In-Memory Computing.
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

Gradient-Based Novelty Detection Boosted by Self-Supervised Binary Classification.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Structured Pruning of RRAM Crossbars for Efficient In-Memory Computing Acceleration of Deep Neural Networks.
IEEE Trans. Circuits Syst. II Express Briefs, 2021

GROWN: GRow Only When Necessary for Continual Learning.
CoRR, 2021

RA-BNN: Constructing Robust & Accurate Binary Neural Network to Simultaneously Defend Adversarial Bit-Flip Attack and Improve Accuracy.
CoRR, 2021

Self-supervised Novelty Detection for Continual Learning: A Gradient-Based Approach Boosted by Binary Classification.
Proceedings of the Continual Semi-Supervised Learning - First International Workshop, 2021

MetaGater: Fast Learning of Conditional Channel Gated Networks via Federated Meta-Learning.
Proceedings of the IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems, 2021

KSM: Fast Multiple Task Adaption via Kernel-Wise Soft Mask Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Dynamic Neural Network to Enable Run-Time Trade-off between Accuracy and Latency.
Proceedings of the ASPDAC '21: 26th Asia and South Pacific Design Automation Conference, 2021

2020
Sparse BD-Net: A Multiplication-less DNN with Sparse Binarized Depth-wise Separable Convolution.
ACM J. Emerg. Technol. Comput. Syst., 2020

DA2: Deep Attention Adapter for Memory-EfficientOn-Device Multi-Domain Learning.
CoRR, 2020

A Progressive Sub-Network Searching Framework for Dynamic Inference.
CoRR, 2020

Processing-in-Memory Accelerator for Dynamic Neural Network with Run-Time Tuning of Accuracy, Power and Latency.
Proceedings of the 33rd IEEE International System-on-Chip Conference, 2020

Robust Sparse Regularization: Defending Adversarial Attacks Via Regularized Sparse Network.
Proceedings of the GLSVLSI '20: Great Lakes Symposium on VLSI 2020, 2020

Non-uniform DNN Structured Subnets Sampling for Dynamic Inference.
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

A Flexible Processing-in-Memory Accelerator for Dynamic Channel-Adaptive Deep Neural Networks.
Proceedings of the 25th Asia and South Pacific Design Automation Conference, 2020

Harmonious Coexistence of Structured Weight Pruning and Ternarization for Deep Neural Networks.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness.
CoRR, 2019

Binarized Depthwise Separable Neural Network for Object Tracking in FPGA.
Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019

2018
A Fully Onchip Binarized Convolutional Neural Network FPGA Impelmentation with Accurate Inference.
Proceedings of the International Symposium on Low Power Electronics and Design, 2018


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