Tao Lin

According to our database, Tao Lin authored at least 54 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2026

Improving Model Fusion by Training-Time Neuron Alignment With Fixed Neuron Anchors.

Zexi Li, Zhiqi Li, Jie Lin, Tao Shen, Jun Xiao, Yike Guo, Tao Lin, Chao Wu

IEEE Trans. Pattern Anal. Mach. Intell., March, 2026

2025

PathBench: Advancing the Benchmark of Large Multimodal Models for Pathology Image Understanding at Patch and Whole Slide Level.

Yuxuan Sun, Hao Wu, Chenglu Zhu, Yixuan Si, Qizi Chen, Yunlong Zhang, Kai Zhang, Jingxiong Li, Jiatong Cai, Yuhan Wang, Lin Sun, Tao Lin, Lin Yang

IEEE Trans. Medical Imaging, October, 2025

Decentralized gradient tracking with local steps.

Yue Liu, Tao Lin, Anastasia Koloskova, Sebastian U. Stich

Optim. Methods Softw., September, 2025

Camouflaged Variational Graph AutoEncoder Against Attribute Inference Attacks for Cross-Domain Recommendation.

Yudi Xiong, Yongxin Guo, Weike Pan, Qiang Yang, Zhong Ming, Xiaojin Zhang, Han Yu, Tao Lin, Xiaoying Tang

IEEE Trans. Knowl. Data Eng., July, 2025

Open Source AI-based SE Tools: Opportunities and Challenges of Collaborative Software Learning.

Zhihao Lin, Wei Ma, Tao Lin, Yaowen Zheng, Jingquan Ge, Jun Wang, Jacques Klein, Tegawendé F. Bissyandé, Yang Liu, Li Li

ACM Trans. Softw. Eng. Methodol., June, 2025

CPathAgent: An Agent-based Foundation Model for Interpretable High-Resolution Pathology Image Analysis Mimicking Pathologists' Diagnostic Logic.

Yuxuan Sun, Yixuan Si, Chenglu Zhu, Kai Zhang, Zhongyi Shui, Bowen Ding, Tao Lin, Lin Yang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Beyond Right to be Forgotten: Managing Heterogeneity Side Effects Through Strategic Incentives.

Jiaqi Shao, Tao Lin, Xiaojin Zhang, Qiang Yang, Bing Luo

Proceedings of the Twenty-sixth International Symposium on Theory, 2025

FedGuCci: Making Local Models More Connected in Landscape for Federated Learning.

Zexi Li, Jie Lin, Zhiqi Li, Didi Zhu, Tao Shen, Tao Lin, Chao Wu, Nicholas D. Lane

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration.

Yuxuan Sun, Yunlong Zhang, Yixuan Si, Chenglu Zhu, Kai Zhang, Zhongyi Shui, Jingxiong Li, Xuan Gong, Xinheng Lyu, Tao Lin, Lin Yang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models.

Yongxin Guo, Zhenglin Cheng, Xiaoying Tang, Zhaopeng Tu, Tao Lin

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Enhancing Clustered Federated Learning: Integration of Strategies and Improved Methodologies.

Yongxin Guo, Xiaoying Tang, Tao Lin

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing.

Yongxin Guo, Lin Wang, Xiaoying Tang, Tao Lin

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

IPIGuard: A Novel Tool Dependency Graph-Based Defense Against Indirect Prompt Injection in LLM Agents.

Hengyu An, Jinghuai Zhang, Tianyu Du, Chunyi Zhou, Qingming Li, Tao Lin, Shouling Ji

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology.

Yuxuan Sun, Yixuan Si, Chenglu Zhu, Xuan Gong, Kai Zhang, Pingyi Chen, Ye Zhang, Zhongyi Shui, Tao Lin, Lin Yang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration.

Yuxuan Sun, Yunlong Zhang, Yixuan Si, Chenglu Zhu, Zhongyi Shui, Kai Zhang, Jingxiong Li, Xingheng Lyu, Tao Lin, Lin Yang

CoRR, 2024

Training-time Neuron Alignment through Permutation Subspace for Improving Linear Mode Connectivity and Model Fusion.

Zexi Li, Zhiqi Li, Jie Lin, Tao Shen, Tao Lin, Chao Wu

CoRR, 2024

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering.

Yongxin Guo, Xiaoying Tang, Tao Lin

Proceedings of the Forty-first International Conference on Machine Learning, 2024

PathMMU: A Massive Multimodal Expert-Level Benchmark for Understanding and Reasoning in Pathology.

Yuxuan Sun, Hao Wu, Chenglu Zhu, Sunyi Zheng, Qizi Chen, Kai Zhang, Yunlong Zhang, Dan Wan, Xiaoxiao Lan, Mengyue Zheng, Jingxiong Li, Xinheng Lyu, Tao Lin, Lin Yang

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Find Your Optimal Assignments On-the-fly: A Holistic Framework for Clustered Federated Learning.

Yongxin Guo, Xiaoying Tang, Tao Lin

CoRR, 2023

FedConceptEM: Robust Federated Learning Under Diverse Distribution Shifts.

Yongxin Guo, Xiaoying Tang, Tao Lin

CoRR, 2023

DELTA: Diverse Client Sampling for Fasting Federated Learning.

Lin Wang, Yongxin Guo, Tao Lin, Xiaoying Tang

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

Revisiting Weighted Aggregation in Federated Learning with Neural Networks.

Zexi Li, Tao Lin, Xinyi Shang, Chao Wu

Proceedings of the International Conference on Machine Learning, 2023

FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction.

Yongxin Guo, Xiaoying Tang, Tao Lin

Proceedings of the International Conference on Machine Learning, 2023

No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier.

Zexi Li, Xinyi Shang, Rui He, Tao Lin, Chao Wu

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

2022

Algorithms for Efficient and Robust Distributed Deep Learning.

Tao Lin

PhD thesis, 2022

Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition.

Jie Su, Zhenyu Wen, Tao Lin, Yu Guan

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2022

Client Selection in Nonconvex Federated Learning: Improved Convergence Analysis for Optimal Unbiased Sampling Strategy.

Lin Wang, Yongxin Guo, Tao Lin, Xiaoying Tang

CoRR, 2022

FedAug: Reducing the Local Learning Bias Improves Federated Learning on Heterogeneous Data.

Yongxin Guo, Tao Lin, Xiaoying Tang

CoRR, 2022

2021

Towards Federated Learning on Time-Evolving Heterogeneous Data.

Yongxin Guo, Tao Lin, Xiaoying Tang

CoRR, 2021

Understanding Memorization from the Perspective of Optimization via Efficient Influence Estimation.

Futong Liu, Tao Lin, Martin Jaggi

CoRR, 2021

Representation Memorization for Fast Learning New Knowledge without Forgetting.

Fei Mi, Tao Lin, Boi Faltings

CoRR, 2021

RelaySum for Decentralized Deep Learning on Heterogeneous Data.

Thijs Vogels, Lie He, Anastasia Koloskova, Sai Praneeth Karimireddy, Tao Lin, Sebastian U. Stich, Martin Jaggi

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

An Improved Analysis of Gradient Tracking for Decentralized Machine Learning.

Anastasia Koloskova, Tao Lin, Sebastian U. Stich

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

Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data.

Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi

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

Consensus Control for Decentralized Deep Learning.

Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich

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

2020

GA-Par: Dependable Microservice Orchestration Framework for Geo-Distributed Clouds.

Zhenyu Wen, Tao Lin, Renyu Yang, Shouling Ji, Rajiv Ranjan, Alexander B. Romanovsky, Chang-Ting Lin, Jie Xu

IEEE Trans. Parallel Distributed Syst., 2020

Masking as an Efficient Alternative to Finetuning for Pretrained Language Models.

Mengjie Zhao, Tao Lin, Martin Jaggi, Hinrich Schütze

CoRR, 2020

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them.

Chen Liu, Mathieu Salzmann, Tao Lin, Ryota Tomioka, Sabine Süsstrunk

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Ensemble Distillation for Robust Model Fusion in Federated Learning.

Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Extrapolation for Large-batch Training in Deep Learning.

Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi

Proceedings of the 37th International Conference on Machine Learning, 2020

Don't Use Large Mini-batches, Use Local SGD.

Tao Lin, Sebastian U. Stich, Kumar Kshitij Patel, Martin Jaggi

Proceedings of the 8th International Conference on Learning Representations, 2020

Dynamic Model Pruning with Feedback.

Tao Lin, Sebastian U. Stich, Luis Barba, Daniil Dmitriev, Martin Jaggi

Proceedings of the 8th International Conference on Learning Representations, 2020

Decentralized Deep Learning with Arbitrary Communication Compression.

Anastasia Koloskova, Tao Lin, Sebastian U. Stich, Martin Jaggi

Proceedings of the 8th International Conference on Learning Representations, 2020

Masking as an Efficient Alternative to Finetuning for Pretrained Language Models.

Mengjie Zhao, Tao Lin, Fei Mi, Martin Jaggi, Hinrich Schütze

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Generalized Class Incremental Learning.

Fei Mi, Lingjing Kong, Tao Lin, Kaicheng Yu, Boi Faltings

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Exploring interpretable LSTM neural networks over multi-variable data.

Tian Guo, Tao Lin, Nino Antulov-Fantulin

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Don't Use Large Mini-Batches, Use Local SGD.

Tao Lin, Sebastian U. Stich, Martin Jaggi

CoRR, 2018

Multi-variable LSTM neural network for autoregressive exogenous model.

Tian Guo, Tao Lin

CoRR, 2018

End-to-End DNN Training with Block Floating Point Arithmetic.

Mario Drumond, Tao Lin, Martin Jaggi, Babak Falsafi

CoRR, 2018

Training DNNs with Hybrid Block Floating Point.

Mario Drumond, Tao Lin, Martin Jaggi, Babak Falsafi

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

An interpretable LSTM neural network for autoregressive exogenous model.

Tian Guo, Tao Lin, Yao Lu

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Heterogeneous Recommendations: What You Might Like To Read After Watching Interstellar.

Rachid Guerraoui, Anne-Marie Kermarrec, Tao Lin, Rhicheek Patra

Proc. VLDB Endow., 2017

Fog Orchestration for Internet of Things Services.

Zhenyu Wen, Renyu Yang, Peter Garraghan, Tao Lin, Jie Xu, Michael Rovatsos

IEEE Internet Comput., 2017

Hybrid Neural Networks for Learning the Trend in Time Series.

Tao Lin, Tian Guo, Karl Aberer

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017