Tianyun Zhang

Orcid: 0000-0002-2475-6414

According to our database1, Tianyun Zhang authored at least 44 papers between 2011 and 2024.

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Bibliography

2024
Segmentation of Low-Light Optical Coherence Tomography Angiography Images under the Constraints of Vascular Network Topology.
Sensors, February, 2024

2023
DEFN: Dual-Encoder Fourier Group Harmonics Network for Three-Dimensional Macular Hole Reconstruction with Stochastic Retinal Defect Augmentation and Dynamic Weight Composition.
CoRR, 2023

Defense against Adversarial Cloud Attack on Remote Sensing Salient Object Detection.
CoRR, 2023

Deep Transfer Learning for Intelligent Vehicle Perception: a Survey.
CoRR, 2023

RXFOOD: Plug-in RGB-X Fusion for Object of Interest Detection.
CoRR, 2023

Automatic Subnetwork Search Through Dynamic Differentiable Neuron Pruning.
Proceedings of the 24th International Symposium on Quality Electronic Design, 2023

Semi-Supervised Graph Ultra-Sparsifier Using Reweighted ℓ1 Optimization.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
StructADMM: Achieving Ultrahigh Efficiency in Structured Pruning for DNNs.
IEEE Trans. Neural Networks Learn. Syst., 2022

Graph sparsification with graph convolutional networks.
Int. J. Data Sci. Anal., 2022

When 360-degree video meets 5G: a measurement study of delay in live streaming.
Proceedings of the MobiArch '22: Proceedings of the 17th ACM Workshop on Mobility in the Evolving Internet Architecture, 2022

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

Compact Multi-level Sparse Neural Networks with Input Independent Dynamic Rerouting.
Proceedings of the 34th IEEE International Conference on Tools with Artificial Intelligence, 2022

AdverSparse: An Adversarial Attack Framework for Deep Spatial-Temporal Graph Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2022

Loss Attitude Aware Energy Management for Signal Detection.
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021
Load-balanced Gather-scatter Patterns for Sparse Deep Neural Networks.
CoRR, 2021

Adversarial Attack Generation Empowered by Min-Max Optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Towards AQFP-Capable Physical Design Automation.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

2020
Computation on Sparse Neural Networks: an Inspiration for Future Hardware.
CoRR, 2020

A Unified DNN Weight Compression Framework Using Reweighted Optimization Methods.
CoRR, 2020

BLK-REW: A Unified Block-based DNN Pruning Framework using Reweighted Regularization Method.
CoRR, 2020

An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices.
CoRR, 2020

SGCN: A Graph Sparsifier Based on Graph Convolutional Networks.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

An Image Enhancing Pattern-Based Sparsity for Real-Time Inference on Mobile Devices.
Proceedings of the Computer Vision - ECCV 2020, 2020

INVITED: Computation on Sparse Neural Networks and its Implications for Future Hardware.
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

On the Optimal Interdiction of Transportation Networks.
Proceedings of the 2020 American Control Conference, 2020

2019
Beyond Adversarial Training: Min-Max Optimization in Adversarial Attack and Defense.
CoRR, 2019

Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM.
CoRR, 2019

State Evaluation of Power Transformer Based on Digital Twin.
Proceedings of the 2019 IEEE International Conference on Service Operations and Logistics, 2019

An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM.
Proceedings of the 2019 IEEE/ACM International Symposium on Low Power Electronics and Design, 2019

Generation of Low Distortion Adversarial Attacks via Convex Programming.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Data Temperature-Aware Bloom Filters for Flash-Based Storage.
Proceedings of the 21st IEEE International Conference on High Performance Computing and Communications; 17th IEEE International Conference on Smart City; 5th IEEE International Conference on Data Science and Systems, 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

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Methods of Multipliers.
Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems, 2019

2018
ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers.
CoRR, 2018

A Unified Framework of DNN Weight Pruning and Weight Clustering/Quantization Using ADMM.
CoRR, 2018

Progressive Weight Pruning of Deep Neural Networks using ADMM.
CoRR, 2018

ADAM-ADMM: A Unified, Systematic Framework of Structured Weight Pruning for DNNs.
CoRR, 2018

Systematic Weight Pruning of DNNs using Alternating Direction Method of Multipliers.
Proceedings of the 6th International Conference on Learning Representations, 2018

Reinforced Adversarial Attacks on Deep Neural Networks Using ADMM.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

A Systematic DNN Weight Pruning Framework Using Alternating Direction Method of Multipliers.
Proceedings of the Computer Vision - ECCV 2018, 2018

2011
A method to build reconfigurable architectures by extracting common subgraphs.
Proceedings of the 2011 IEEE 9th International Conference on ASIC, 2011


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