林涛博士

Tao Lin, Ph.D.

学习与推理系统实验室

联系

邮箱: lintao@westlake.edu.cn

网站: https://lins-lab.github.io/

林涛博士

Tao Lin, Ph.D.

学习与推理系统实验室

联系

邮箱: lintao@westlake.edu.cn

网站: https://lins-lab.github.io/

Simplicity is the ultimate sophistication. ---Leonardo da Vinci

个人简介


    林涛博士2014年毕业于浙江大学电气工程学院,并分别于2017年和2022年在瑞士洛桑联邦理工学院(EPFL)获得硕士与博士学位。林涛博士于2022年11月正式加入西湖大学工学院,任特聘研究员、助理教授、博士生导师,并独立创建西湖大学“学习与推理系统实验室”(Learning and INference Systems (LINs) Laboratory)。


学术成果


林涛博士的研究领域为(1)深度学习与优化,和(2)分布式深度学习与推理系统。相关成果达20余篇论文,其中以一作/共同一作身份在顶级机器学习会议如ICML/NeurIPS/ICLR上发表论文10余篇。根据谷歌学术统计,论文引用达2500余次(截至2023年08月),H指数20。


代表论文(*代表共同一作,#代表通信作者


1. Hao Zhao, Yuejiang Liu, Alexandre Alahi, Tao Lin#. "On Pitfalls of Test-time Adaptation." ICML 2023

2. Liangze Jiang*, Tao Lin*#. "Test-Time Robust Personalization for Federated Learning." ICLR 2023.

3. Thijs Vogels*, Lie He*, Anastasia Koloskova, Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi. "RelaySum for Decentralized Deep Learning on Heterogeneous Data." NeurIPS 2021.

4. Tao Lin#, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi. "Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data." ICML 2021.

5. Lingjing Kong*, Tao Lin*#, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich. "Consensus Control for Decentralized Deep Learning." ICML 2021.

6. Tao Lin*#, Lingjing Kong*, Sebastian U. Stich, Martin Jaggi. "Ensemble Distillation for Robust Model Fusion in Federated Learning." NeurIPS 2020.

7. Mengjie Zhao*, Tao Lin*, Fei Mi, Martin Jaggi, Hinrich Schütze. "Masking as an Efficient Alternative to Finetuning for Pretrained Language Models." EMNLP 2020.

8. Tao Lin*#, Lingjing Kong*, Sebastian U. Stich, Martin Jaggi. "Extrapolation for Large-batch Training in Deep Learning." ICML 2020.

9. Tao Lin#, Sebastian U. Stich, Luis Barba, Daniil Dmitriev, Martin Jaggi. "Dynamic Model Pruning with Feedback." ICLR 2020.

10. Anastasia Koloskova*, Tao Lin*, Sebastian U. Stich, Martin Jaggi. "Decentralized Deep Learning with Arbitrary Communication Compression." ICLR 2020.

11. Tao Lin#, Sebastian U. Stich, Kumar Kshitij Patel, Martin Jaggi. "Don't Use Large Mini-Batches, Use Local SGD." ICLR 2020.

12. Tian Guo, Tao Lin, Nino Antulov-Fantulin. "Exploring Interpretable LSTM Neural Networks over Multi-Variable Data." ICML 2019.

13. Tao Lin*#, Tian Guo*, Karl Aberer. "Hybrid Neural Networks for Learning the Trend in Time Series." IJCAI 2017.


联系方式


  电子邮箱:lintao@westlake.edu.cn

林涛课题组拟长期开展高效可靠的深度学习与推理系统方面的研究。现课题组诚聘上述研究方向的杰出人才,作为博士后,博士研究生,科研助理,实习生(最少3个月)以及访问学生,来加入我们。申请者请将材料发送至lins-lab.hr@westlake.edu.cn并同步抄送至lintao@westlake.edu.cn。更多信息请访问课题组主页:https://lins-lab.github.io/openings/