Publications

publications by categories in reversed chronological order. * denotes equal contribution; † denotes corresponding authorship.

2023

    2022

    1. preprint
      Test-Time Robust Personalization for Federated Learning
      Jiang, Liangze*, and Lin, Tao*†
      arXiv preprint arXiv:2205.10920 2022
      PDF Code
    2. IMWUT 2022
      Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition
      Su, Jie, Wen, Zhenyu, Lin, Tao, and Guan, Yu
      Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 2022
      PDF Code
    3. preprint
      DELTA: Diverse Client Sampling for Fasting Federated Learning
      Wang, Lin, Guo, YongXin, Lin, Tao, and Tang, Xiaoying
      arXiv preprint arXiv:2205.13925 2022
    4. preprint
      FedDebias: Reducing the Local Learning Bias Improves Federated Learning on Heterogeneous Data
      Guo, Yongxin, Tang, Xiaoying, and Lin, Tao
      arXiv preprint arXiv:2205.13462 2022
    5. preprint
      Understanding the Training Dynamics in Federated Deep Learning via Aggregation Weight Optimization
      Li, Zexi, Lin, Tao, Shang, Xinyi, and Wu, Chao
      2022
    6. OPT 2022
      Decentralized Stochastic Optimization with Client Sampling
      Liu, Ziwei, Koloskova, Anastasia, Jaggi, Martin, and Lin, Tao†
      Optimization and machine learning (OPT) workshop, in NeurIPS 2022
      PDF
    7. preprint
      Decentralized Gradient Tracking with Local Steps
      Liu, Yue, Lin, Tao, Koloskova, Anastasia, and Stich, Sebastian U.
      2022
      PDF

    2021

    1. preprint
      Towards Federated Learning on Time-Evolving Heterogeneous Data
      Guo, Yongxin*, Lin, Tao*, and Tang, Xiaoying
      arXiv preprint arXiv:2112.13246, appeared in FL-ICML workshop 2021
      PDF
    2. NeurIPS 2021
      RelaySum for Decentralized Deep Learning on Heterogeneous Data
      Vogels, Thijs*, He, Lie*, Koloskova, Anastasia, Lin, Tao, Karimireddy, Sai Praneeth, Stich, Sebastian U., and Jaggi, Martin
      In Advances in Neural Information Processing Systems (NeurIPS) 2021
      PDF Code Video Slides
    3. NeurIPS 2021
      An Improved Analysis of Gradient Tracking for Decentralized Machine Learning
      Koloskova, Anastasia, Lin, Tao, and Stich, Sebastian U.
      In Advances in Neural Information Processing Systems (NeurIPS) 2021
      PDF
    4. ICML 2021
      Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
      Lin, Tao, Karimireddy, Sai Praneeth, Stich, Sebastian U., and Jaggi, Martin
      In International Conference on Machine Learning (ICML) 2021
      PDF Code
    5. ICML 2021
      Consensus Control for Decentralized Deep Learning
      Kong, Lingjing*, Lin, Tao*†, Koloskova, Anastasia, Jaggi, Martin, and Stich, Sebastian U.
      In International Conference on Machine Learning (ICML) 2021
      PDF
    6. OPT 2021
      Understanding Memorization from the Perspective of Optimization via Efficient Influence Estimation
      Liu, Futong, Lin, Tao†, and Jaggi, Martin
      Optimization and machine learning (OPT) workshop, in NeurIPS 2021
      PDF

    2020

    1. NeurIPS 2020
      Ensemble Distillation for Robust Model Fusion in Federated Learning
      Lin, Tao*†, Kong, Lingjing*, Stich, Sebastian U, and Jaggi, Martin
      In Advances in Neural Information Processing Systems (NeurIPS) 2020
      PDF Code
    2. NeurIPS 2020
      On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them
      Liu, Chen, Salzmann, Mathieu, Lin, Tao, Tomioka, Ryota, and Süsstrunk, Sabine
      In Advances in Neural Information Processing Systems (NeurIPS) 2020
      PDF Code
    3. EMNLP 2020
      Masking as an Efficient Alternative to Finetuning for Pretrained Language Models
      Zhao, Mengjie*, Lin, Tao*, Jaggi, Martin, and Schütze, Hinrich
      In Empirical Methods in Natural Language Processing (EMNLP) 2020
      PDF Code
    4. ICML 2020
      Extrapolation for Large-batch Training in Deep Learning
      Lin, Tao*†, Kong, Lingjing*, Stich, Sebastian U., and Jaggi, Martin
      In International Conference on Machine Learning (ICML) 2020
      PDF
    5. ICLR 2020
      Dynamic Model Pruning with Feedback
      Lin, Tao, Stich, Sebastian U, Barba, Luis, Dmitriev, Daniil, and Jaggi, Martin
      In International Conference on Learning Representations (ICLR) 2020
      PDF Code
    6. ICLR 2020
      Decentralized Deep Learning with Arbitrary Communication Compression
      Koloskova, Anastasia*, Lin, Tao*, Stich, Sebastian U, and Jaggi, Martin
      In International Conference on Learning Representations (ICLR) 2020
      PDF Code
    7. ICLR 2020
      Don’t Use Large Mini-batches, Use Local SGD
      Lin, Tao, Stich, Sebastian U, Patel, Kumar Kshitij, and Jaggi, Martin
      In International Conference on Learning Representations (ICLR) 2020
      PDF Code
    8. CLVision 2020
      Generalized Class Incremental Learning
      Mi, Fei*, Kong, Lingjing*, Lin, Tao, Yu, Kaicheng, and Faltings, Boi
      In Conference on Computer Vision and Pattern Recognition (CVPR) Workshop on Continual Learning 2020
      PDF

    2019

    1. ICML 2019
      Exploring Interpretable LSTM Neural Networks over Multi-variable Data
      Guo, Tian, Lin, Tao, and Antulov-Fantulin, Nino
      In International Conference on Machine Learning (ICML) 2019
      PDF Code
    2. TPDS 2019
      Ga-par: Dependable Microservice Orchestration Framework for Geo-distributed Clouds
      Wen, Zhenyu, Lin, Tao, Yang, Renyu, Ji, Shouling, Ranjan, Rajiv, Romanovsky, Alexander, Lin, Changting, and Xu, Jie
      IEEE Transactions on Parallel and Distributed Systems (TPDS) 2019
      PDF

    2018

    1. NeurIPS 2019
      Training DNNs with Hybrid Block Floating Point
      Drumond, Mario, Lin, Tao, Jaggi, Martin, and Falsafi, Babak
      In Advances in Neural Information Processing Systems (NeurIPS) 2018
      PDF Code

    2017

    1. IJCAI 2017
      Hybrid Neural Networks for Learning the Trend in Time Series
      Lin, Tao*, Guo, Tian*, and Aberer, Karl
      In Proceedings of the twenty-sixth international joint conference on artificial intelligence (IJCAI) 2017
      PDF
    2. VLDB 2017
      Heterogeneous Recommendations: What You Might Like to Read after Watching Interstellar
      Guerraoui, Rachid, Kermarrec, Anne-Marie, Lin, Tao, and Patra, Rhicheek
      Proceedings of the Very Large Data Base Endowment (VLDB) 2017
      PDF Supp Code Slides
    3. IEEE 2017
      Fog Orchestration for IoT Services: Issues, Challenges and Directions
      Wen, Zhenyu, Yang, Renyu, Garraghan, Peter, Lin, Tao, Xu, Jie, and Rovatsos, Michael
      IEEE Internet Computing 2017
      PDF