Lu Yin

According to our database, Lu Yin authored at least 22 papers between 2020 and 2024.

Collaborative distances:

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

2024

A Structural-Clustering Based Active Learning for Graph Neural Networks.

Ricky Maulana Fajri, Yulong Pei, Lu Yin, Mykola Pechenizkiy

Proceedings of the Advances in Intelligent Data Analysis XXII, 2024

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

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

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

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

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

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

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

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

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

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

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

Proceedings of the Uncertainty in Artificial Intelligence, 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

Semantic-Based Few-Shot Classification by Psychometric Learning.

Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy

Proceedings of the Advances in Intelligent Data Analysis XX, 2022

2021

Semantic-Based Few-Shot Learning by Interactive Psychometric Testing.

Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy

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

Hierarchical Semantic Segmentation using Psychometric Learning.

Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy

Proceedings of the Asian Conference on Machine Learning, 2021

2020

Knowledge Elicitation Using Deep Metric Learning and Psychometric Testing.

Lu Yin, Vlado Menkovski, Mykola Pechenizkiy

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

Beyond Labels: Knowledge Elicitation using Deep Metric Learning and Psychometric Testing.

Lu Yin

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