Publications

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

2024

  1. CVPR 2024
    On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm
    Sun, Peng, Shi, Bei, Yu, Daiwei, and Lin, Tao†
    In Computer Vision and Pattern Recognition Conference (CVPR) 2024
  2. ICLR 2024
    Towards Robust Multi-Modal Reasoning via Model Selection
    Liu, Xiangyan*, Li, Rongxue*, Ji, Wei, and Lin, Tao†
    In International Conference on Learning Representations (ICLR) 2024
  3. ICLR 2024
    Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
    Song, Haobo*, Zhao, Hao*, Majumder, Soumajit, and Lin, Tao†
    In International Conference on Learning Representations (ICLR) 2024
  4. preprint
    Training-time Neuron Alignment for Improving Linear Mode Connectivity and Model Fusion
    Li, Zexi, Li, Zhiqi, Lin, Jie, Shen, Tao, Lin, Tao†, and Wu, Chao†
    preprint 2024
  5. preprint
    Federated Unlearning: a Perspective of Stability and Fairness
    2024

2023

  1. NeurIPS 2023
    DELTA: Diverse Client Sampling for Fasting Federated Learning
    Wang, Lin, Guo, YongxinLin, Tao, and Tang, Xiaoying
    In Advances in Neural Information Processing Systems (NeurIPS) 2023
  2. ICCV 2023
    No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier
    In International Conference on Computer Vision (ICCV) 2023
  3. ICML 2023
    On Pitfalls of Test-time Adaptation
    In International Conference on Machine Learning (ICML), abridged in ICLR Workshop on Trustworthy ML 2023 and ICLR Workshop on DG (spotlight) 2023
  4. ICML 2023
    FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction
    In International Conference on Machine Learning (ICML) 2023
  5. ICML 2023
    Revisiting Weighted Aggregation in Federated Learning with Neural Networks
    In International Conference on Machine Learning (ICML) 2023
  6. ICLR 2023
    Test-Time Robust Personalization for Federated Learning
    In International Conference on Learning Representations (ICLR) 2023
  7. preprint
    FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering
    preprint (arXiv:2301.12379), appeared in ICLR Workshop ML4IoT 2023
  8. preprint
    Find Your Optimal Assignments On-the-fly: A Holistic Framework for Clustered Federated Learning
    preprint (arXiv:2310.05397) 2023
  9. preprint
    Revisiting Implicit Models: Sparsity Trade-offs Capability in Weight-tied Model
    Song, Haobo, Majumder, Soumajit, and Lin, Tao†
    appeared in ICLR Workshop SNN 2023
  10. preprint
    Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging
    In 2023

2022

  1. preprint
    Decentralized Gradient Tracking with Local Steps
    preprint (arXiv:2301.01313) 2022
  2. IMWUT 2022
    Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition
    Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 2022
  3. OPT 2022
    Decentralized Stochastic Optimization with Client Sampling
    Optimization and machine learning (OPT) workshop, in NeurIPS 2022

2021

  1. 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
  2. NeurIPS 2021
    RelaySum for Decentralized Deep Learning on Heterogeneous Data
    In Advances in Neural Information Processing Systems (NeurIPS) 2021
  3. NeurIPS 2021
    An Improved Analysis of Gradient Tracking for Decentralized Machine Learning
    In Advances in Neural Information Processing Systems (NeurIPS) 2021
  4. ICML 2021
    Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
    In International Conference on Machine Learning (ICML) 2021
  5. ICML 2021
    Consensus Control for Decentralized Deep Learning
    In International Conference on Machine Learning (ICML) 2021
  6. preprint
    Towards Federated Learning on Time-Evolving Heterogeneous Data
    preprint (arXiv:2112.13246), appeared in FL-ICML workshop 2021

2020

  1. NeurIPS 2020
    Ensemble Distillation for Robust Model Fusion in Federated Learning
    In Advances in Neural Information Processing Systems (NeurIPS) 2020
  2. NeurIPS 2020
    On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them
    In Advances in Neural Information Processing Systems (NeurIPS) 2020
  3. ICML 2020
    Extrapolation for Large-batch Training in Deep Learning
    In International Conference on Machine Learning (ICML) 2020
  4. EMNLP 2020
    Masking as an Efficient Alternative to Finetuning for Pretrained Language Models
    In Empirical Methods in Natural Language Processing (EMNLP) 2020
  5. ICLR 2020
    Decentralized Deep Learning with Arbitrary Communication Compression
    In International Conference on Learning Representations (ICLR) 2020
  6. ICLR 2020
    Don’t Use Large Mini-batches, Use Local SGD
    In International Conference on Learning Representations (ICLR) 2020
  7. ICLR 2020
    Dynamic Model Pruning with Feedback
    In International Conference on Learning Representations (ICLR) 2020
  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

2019

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

2018

  1. NeurIPS 2018
    Training DNNs with Hybrid Block Floating Point
    In Advances in Neural Information Processing Systems (NeurIPS) 2018

2017

  1. IJCAI 2017
    Hybrid Neural Networks for Learning the Trend in Time Series
    In Proceedings of the twenty-sixth international joint conference on artificial intelligence (IJCAI) 2017
  2. IEEE 2017
    Fog Orchestration for IoT Services: Issues, Challenges and Directions
    Wen, Zhenyu, Yang, Renyu, Garraghan, Peter, Lin, TaoXu, Jie, and Rovatsos, Michael
    IEEE Internet Computing 2017
  3. VLDB 2017
    Heterogeneous Recommendations: What You Might Like to Read after Watching Interstellar
    Proceedings of the Very Large Data Base Endowment (VLDB) 2017