Shiwei Liu

According to our database, Shiwei Liu authored at least 72 papers between 2018 and 2024.

Collaborative distances:

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

2024

Hybrid Conditional Kernel SVM for Wire Rope Defect Recognition.

Shiwei Liu, Yong Liu, Longxiang Shan, Qiaohua Wang, Yanhua Sun, Lingsong He

IEEE Trans. Ind. Informatics, April, 2024

HARDSEA: Hybrid Analog-ReRAM Clustering and Digital-SRAM In-Memory Computing Accelerator for Dynamic Sparse Self-Attention in Transformer.

Shiwei Liu, Chen Mu, Hao Jiang, Yunzhengmao Wang, Jinshan Zhang, Feng Lin, Keji Zhou, Qi Liu, Chixiao Chen

IEEE Trans. Very Large Scale Integr. Syst., February, 2024

Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding.

Zhenyu Zhang, Runjin Chen, Shiwei Liu, Zhewei Yao, Olatunji Ruwase, Beidi Chen, Xiaoxia Wu, Zhangyang Wang

CoRR, 2024

ConSmax: Hardware-Friendly Alternative Softmax with Learnable Parameters.

Shiwei Liu, Guanchen Tao, Yifei Zou, Derek Chow, Zichen Fan, Kauna Lei, Bangfei Pan, Dennis Sylvester, Gregory Kielian, Mehdi Saligane

CoRR, 2024

2023

Feedback and contribution of vegetation, air temperature and precipitation to land surface temperature in the Yangtze River Basin considering statistical analysis.

Jinlian Liu, Xinyao Zhou, Hanya Tang, Fengqin Yan, Shiwei Liu, Xuguang Tang, Zhi Ding, Ke Jiang, Pujia Yu

Int. J. Digit. Earth, December, 2023

Future variation of land surface temperature in the Yangtze River Basin based on CMIP6 model.

Jinlian Liu, Hanya Tang, Fengqin Yan, Shiwei Liu, Xuguang Tang, Zhi Ding, Pujia Yu

Int. J. Digit. Earth, December, 2023

A Modified A Posteriori Subcell Limiter for High Order Flux Reconstruction Scheme for One-Dimensional Detonation Simulation.

Shiwei Liu, Li Yuan

J. Sci. Comput., November, 2023

Don't Be So Dense: Sparse-to-Sparse GAN Training Without Sacrificing Performance.

Shiwei Liu, Yuesong Tian, Tianlong Chen, Li Shen

Int. J. Comput. Vis., October, 2023

Wire Rope Defect Recognition Method Based on MFL Signal Analysis and 1D-CNNs.

Shiwei Liu, Muchao Chen

Sensors, April, 2023

Radiative Effects and Costing Assessment of Arctic Sea Ice Albedo Changes.

Hairui Hao, Bo Su, Shiwei Liu, Wenqin Zhuo

Remote. Sens., February, 2023

Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks.

Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu

Trans. Mach. Learn. Res., 2023

Effects of Atmospheric Coherent Time on Inverse Synthetic Aperture Ladar Imaging through Atmospheric Turbulence.

Azezigul Abdukirim, Yichong Ren, Zhiwei Tao, Shiwei Liu, Yanling Li, Hanling Deng, Ruizhong Rao

Remote. Sens., 2023

The Counterattack of CNNs in Self-Supervised Learning: Larger Kernel Size might be All You Need.

Tianjin Huang, Tianlong Chen, Zhangyang Wang, Shiwei Liu

CoRR, 2023

E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation.

Boqian Wu, Qiao Xiao, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Decebal Constantin Mocanu, Maurice van Keulen, Elena Mocanu

CoRR, 2023

Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective.

Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen

CoRR, 2023

Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs.

Yuxin Zhang, Lirui Zhao, Mingbao Lin, Yunyun Sun, Yiwu Yao, Xingjia Han, Jared Tanner, Shiwei Liu, Rongrong Ji

CoRR, 2023

Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity.

Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Mykola Pechenizkiy, Yi Liang, Zhangyang Wang, Shiwei Liu

CoRR, 2023

AdaMerging: Adaptive Model Merging for Multi-Task Learning.

Enneng Yang, Zhenyi Wang, Li Shen, Shiwei Liu, Guibing Guo, Xingwei Wang, Dacheng Tao

CoRR, 2023

Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity.

Lu Yin, Shiwei Liu, Ajay Jaiswal, Souvik Kundu, Zhangyang Wang

CoRR, 2023

Optimized Path Planning for USVs under Ocean Currents.

Behzad Akbari, Ya-Jun Pan, Shiwei Liu, Tianye Wang

CoRR, 2023

Dynamic Sparsity Is Channel-Level Sparsity Learner.

Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu

CoRR, 2023

Are Large Kernels Better Teachers than Transformers for ConvNets?

Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu

CoRR, 2023

Ten Lessons We Have Learned in the New "Sparseland": A Short Handbook for Sparse Neural Network Researchers.

Shiwei Liu, Zhangyang Wang

CoRR, 2023

REST: Enhancing Group Robustness in DNNs Through Reweighted Sparse Training.

Jiaxu Zhao, Lu Yin, Shiwei Liu, Meng Fang, Mykola Pechenizkiy

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Enhancing Adversarial Training via Reweighting Optimization Trajectory.

Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask?

Hoang Pham, The-Anh Ta, Shiwei Liu, Lichuan Xiang, Dung Le, Hongkai Wen, Long Tran-Thanh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model.

Shiwei Liu, Tian Zhu, Milong Ren, Chungong Yu, Dongbo Bu, Haicang Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter.

Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Don't just prune by magnitude! Your mask topology is a secret weapon.

Duc Hoang, Souvik Kundu, Shiwei Liu, Zhangyang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Dynamic Sparsity Is Channel-Level Sparsity Learner.

Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A 28nm 53.8TOPS/W 8b Sparse Transformer Accelerator with In-Memory Butterfly Zero Skipper for Unstructured-Pruned NN and CIM-Based Local-Attention-Reusable Engine.

Shiwei Liu, Peizhe Li, Jinshan Zhang, Yunzhengmao Wang, Haozhe Zhu, Wenning Jiang, Shan Tang, Chixiao Chen, Qi Liu, Ming Liu

Proceedings of the IEEE International Solid- State Circuits Conference, 2023

A Scalable Die-to-Die Interconnect with Replay and Repair Schemes for 2.5D/3D Integration.

Jie Liao, Bo Jiao, Jinshan Zhang, Shiwei Liu, Hao Jiang, Jun Tao, Wenning Jiang, Qi Liu, Lihua Zhang, Haozhe Zhu, Chixiao Chen

Proceedings of the IEEE International Symposium on Circuits and Systems, 2023

Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models.

Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang

Proceedings of the International Conference on Machine Learning, 2023

Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication.

Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang

Proceedings of the International Conference on Machine Learning, 2023

Are Large Kernels Better Teachers than Transformers for ConvNets?

Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu

Proceedings of the International Conference on Machine Learning, 2023

Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!

Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity.

Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Tommi Kärkkäinen, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Revisiting Pruning at Initialization Through the Lens of Ramanujan Graph.

Duc N. M. Hoang, Shiwei Liu, Radu Marculescu, Zhangyang Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers.

Tianlong Chen, Zhenyu Zhang, Ajay Kumar Jaiswal, Shiwei Liu, Zhangyang Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Data Augmented Flatness-aware Gradient Projection for Continual Learning.

Enneng Yang, Li Shen, Zhenyi Wang, Shiwei Liu, Guibing Guo, Xingwei Wang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Many-Task Federated Learning: A New Problem Setting and A Simple Baseline.

Ruisi Cai, Xiaohan Chen, Shiwei Liu, Jayanth Srinivasa, Myungjin Lee, Ramana Kompella, Zhangyang Wang

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

Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost.

Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

A Novel E-Exponential Stochastic Resonance Model and Weak Signal Detection Method for Steel Wire Rope.

Shiwei Liu, Yanhua Sun, Yihua Kang

IEEE Trans. Ind. Electron., 2022

The Response of Land Surface Temperature Changes to the Vegetation Dynamics in the Yangtze River Basin.

Jinlian Liu, Shiwei Liu, Xuguang Tang, Zhi Ding, Mingguo Ma, Pujia Yu

Remote. Sens., 2022

A brain-inspired algorithm for training highly sparse neural networks.

Zahra Atashgahi, Joost Pieterse, Shiwei Liu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy

Mach. Learn., 2022

Energy-efficient adaptive virtual-MIMO transmissions for LoRa uplink systems.

Jinping Niu, Xiang Yang, Shiwei Liu, Yanyan Li, Yi Guo

Digit. Signal Process., 2022

More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity.

Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang

CoRR, 2022

Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training.

Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy, Decebal Constantin Mocanu, Shiwei Liu

CoRR, 2022

Achieving Personalized Federated Learning with Sparse Local Models.

Tiansheng Huang, Shiwei Liu, Li Shen, Fengxiang He, Weiwei Lin, Dacheng Tao

CoRR, 2022

Dynamic Sparse Network for Time Series Classification: Learning What to "See".

Qiao Xiao, Boqian Wu, Yu Zhang, Shiwei Liu, Mykola Pechenizkiy, Elena Mocanu, Decebal Constantin Mocanu

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

You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets.

Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu

Proceedings of the Learning on Graphs Conference, 2022

The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training.

Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy

Proceedings of the Tenth International Conference on Learning Representations, 2022

Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity.

Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu

Proceedings of the Tenth International Conference on Learning Representations, 2022

A 200M-Query-Vector/s Computing-in-RRAM ADC-less k-Nearest-Neighbor Accelerator with Time-Domain Winner-Takes-All Circuits.

Chen Mu, Yunzhengmao Wang, Jiapei Zheng, Shiwei Liu, Keji Zhou, Shan Tang, Chixiao Chen, Qi Liu

Proceedings of the 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2022

2021

Efficient and effective training of sparse recurrent neural networks.

Shiwei Liu, Iftitahu Ni'mah, Vlado Menkovski, Decebal Constantin Mocanu, Mykola Pechenizkiy

Neural Comput. Appl., 2021

Sparse evolutionary deep learning with over one million artificial neurons on commodity hardware.

Shiwei Liu, Decebal Constantin Mocanu, Amarsagar Reddy Ramapuram Matavalam, Yulong Pei, Mykola Pechenizkiy

Neural Comput. Appl., 2021

FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity.

Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu

CoRR, 2021

Sparse Training via Boosting Pruning Plasticity with Neuroregeneration.

Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training.

Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy

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

Selfish Sparse RNN Training.

Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy

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

Systolic-Array Deep-Learning Acceleration Exploring Pattern-Indexed Coordinate-Assisted Sparsity for Real-Time On-Device Speech Processing.

Shiwei Liu, Zihao Zhao, Yanhong Wang, Qiaosha Zou, Yiyun Zhang, C.-J. Richard Shi

Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021

Hierarchical Semantic Segmentation using Psychometric Learning.

Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy

Proceedings of the Asian Conference on Machine Learning, 2021

2020

A Wideband Electrical Impedance Tomography System Based on Sensitive Bioimpedance Spectrum Bandwidth.

Chao Tan, Shiwei Liu, Jiabin Jia, Feng Dong

IEEE Trans. Instrum. Meas., 2020

A Communication-Aware DNN Accelerator on ImageNet Using In-Memory Entry-Counting Based Algorithm-Circuit-Architecture Co-Design in 65-nm CMOS.

Haozhe Zhu, Chixiao Chen, Shiwei Liu, Qiaosha Zou, Mingyu Wang, Lihua Zhang, Xiaoyang Zeng, Chuanjin Richard Shi

IEEE J. Emerg. Sel. Topics Circuits Syst., 2020

Topological Insights in Sparse Neural Networks.

Shiwei Liu, Tim van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu

CoRR, 2020

Topological Insights into Sparse Neural Networks.

Shiwei Liu, Tim van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Learning Sparse Neural Networks for Better Generalization.

Shiwei Liu

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Network Performance Optimization with Real Time Traffic Prediction in Data Center Network.

Fulong Yan, Shiwei Liu, Nicola Calabretta

Proceedings of the European Conference on Optical Communications, 2020

XNORAM: An Efficient Computing-in-Memory Architecture for Binary Convolutional Neural Networks with Flexible Dataflow Mapping.

Shiwei Liu, Haozhe Zhu, Chixiao Chen, Lihua Zhang, C.-J. Richard Shi

Proceedings of the 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2020

2019

On improving deep learning generalization with adaptive sparse connectivity.

Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy

CoRR, 2019

Intrinsically Sparse Long Short-Term Memory Networks.

Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy

CoRR, 2019

2018

Wideband chirp excitation source for bioelectrical impedance spectrum tomography.

Shiwei Liu, Chao Tan, Hao Wu, Feng Dong, Jiabin Jia

Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2018