Miao Yin

Orcid: 0000-0002-5554-5417

According to our database1, Miao Yin authored at least 35 papers between 2017 and 2024.

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

Timeline

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Bibliography

2024
MoE-I<sup>2</sup>: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition.
CoRR, 2024

Enhancing Lossy Compression Through Cross-Field Information for Scientific Applications.
CoRR, 2024

NeurLZ: On Enhancing Lossy Compression Performance based on Error-Controlled Neural Learning for Scientific Data.
CoRR, 2024

ELRT: Efficient Low-Rank Training for Compact Convolutional Neural Networks.
CoRR, 2024

PointMLFF: Robust Point Cloud Analysis Based on Multi-Level Feature Fusion.
Proceedings of the International Joint Conference on Neural Networks, 2024

GWLZ: A Group-wise Learning-based Lossy Compression Framework for Scientific Data.
Proceedings of the 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures, 2024

MoE-I²: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

SmartMem: Layout Transformation Elimination and Adaptation for Efficient DNN Execution on Mobile.
Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2023
Online Reviews Sentiment Analysis and Product Feature Improvement with Deep Learning.
ACM Trans. Asian Low Resour. Lang. Inf. Process., August, 2023

Algorithm and hardware co-design co-optimization framework for LSTM accelerator using quantized fully decomposed tensor train.
Internet Things, July, 2023

Projected Generative Adversarial Network for Point Cloud Completion.
IEEE Trans. Circuits Syst. Video Technol., February, 2023

TDC: Towards Extremely Efficient CNNs on GPUs via Hardware-Aware Tucker Decomposition.
Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 2023

GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ETTE: Efficient Tensor-Train-based Computing Engine for Deep Neural Networks.
Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023

COMCAT: Towards Efficient Compression and Customization of Attention-Based Vision Models.
Proceedings of the International Conference on Machine Learning, 2023

GOHSP: A Unified Framework of Graph and Optimization-Based Heterogeneous Structured Pruning for Vision Transformer.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

HALOC: Hardware-Aware Automatic Low-Rank Compression for Compact Neural Networks.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

CSTAR: Towards Compact and Structured Deep Neural Networks with Adversarial Robustness.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Algorithm and Hardware Co-Design of Energy-Efficient LSTM Networks for Video Recognition With Hierarchical Tucker Tensor Decomposition.
IEEE Trans. Computers, 2022

Algorithm and Hardware Co-Design of Energy-Efficient LSTM Networks for Video Recognition with Hierarchical Tucker Tensor Decomposition.
CoRR, 2022

Robot Motion Planning as Video Prediction: A Spatio-Temporal Neural Network-based Motion Planner.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

A Graph Convolutional Network for Point Cloud Completion.
Proceedings of the 2022 The 5th International Conference on Control and Computer Vision, 2022

HODEC: Towards Efficient High-Order DEcomposed Convolutional Neural Networks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

BATUDE: Budget-Aware Neural Network Compression Based on Tucker Decomposition.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Allocating a fixed cost across decision making units with explicitly considering efficiency rankings.
J. Oper. Res. Soc., 2021

CHIP: CHannel Independence-based Pruning for Compact Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards Efficient Tensor Decomposition-Based DNN Model Compression With Optimization Framework.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Towards Extremely Compact RNNs for Video Recognition With Fully Decomposed Hierarchical Tucker Structure.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Doubly Residual Neural Decoder: Towards Low-Complexity High-Performance Channel Decoding.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Compressing Recurrent Neural Networks Using Hierarchical Tucker Tensor Decomposition.
CoRR, 2020

2019
TGAN: Deep Tensor Generative Adversarial Nets for Large Image Generation.
CoRR, 2019

Tensor Super-Resolution with Generative Adversarial Nets: A Large Image Generation Approach.
Proceedings of the Human Brain and Artificial Intelligence - First International Workshop, 2019

High-performance Hardware Architecture for Tensor Singular Value Decomposition: Invited Paper.
Proceedings of the International Conference on Computer-Aided Design, 2019

Tensor Super-resolution for Seismic Data.
Proceedings of the IEEE International Conference on Acoustics, 2019

2017
Seismic facies recognition based on prestack data using deep convolutional autoencoder.
CoRR, 2017


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