Hybrid Neural Networks for Learning the Trend in Time Series. - Tao Lin 004; Tian Guo 002; Karl Aberer (IJCAI, 2017)

Fog Orchestration for Internet of Things Services. - Zhenyu Wen; Renyu Yang; Peter Garraghan; Tao Lin 004; Jie Xu 007; Michael Rovatsos (IEEE Internet Comput., 2017)

Heterogeneous Recommendations: What You Might Like To Read After Watching Interstellar. - Rachid Guerraoui; Anne-Marie Kermarrec; Tao Lin 004; Rhicheek Patra (Proc. VLDB Endow., 2017)

An interpretable LSTM neural network for autoregressive exogenous model. - Tian Guo 002; Tao Lin 004; Yao Lu (ICLR (Workshop), 2018)

Training DNNs with Hybrid Block Floating Point. - Mario Drumond; Tao Lin 004; Martin Jaggi; Babak Falsafi (NeurIPS, 2018)

End-to-End DNN Training with Block Floating Point Arithmetic. - Mario Drumond; Tao Lin 004; Martin Jaggi; Babak Falsafi (CoRR, 2018)

Multi-variable LSTM neural network for autoregressive exogenous model. - Tian Guo 002; Tao Lin 004 (CoRR, 2018)

Don't Use Large Mini-Batches, Use Local SGD. - Tao Lin 004; Sebastian U. Stich; Martin Jaggi (CoRR, 2018)

Exploring interpretable LSTM neural networks over multi-variable data. - Tian Guo 002; Tao Lin 004; Nino Antulov-Fantulin (ICML, 2019)

Generalized Class Incremental Learning. - Fei Mi; Lingjing Kong 001; Tao Lin 004; Kaicheng Yu; Boi Faltings (CVPR Workshops, 2020)

Masking as an Efficient Alternative to Finetuning for Pretrained Language Models. - Mengjie Zhao; Tao Lin 004; Fei Mi; Martin Jaggi; Hinrich Schütze (EMNLP (1), 2020)

Decentralized Deep Learning with Arbitrary Communication Compression. - Anastasia Koloskova; Tao Lin 004; Sebastian U. Stich; Martin Jaggi (ICLR, 2020)

Dynamic Model Pruning with Feedback. - Tao Lin 004; Sebastian U. Stich; Luis Barba; Daniil Dmitriev; Martin Jaggi (ICLR, 2020)

Don't Use Large Mini-batches, Use Local SGD. - Tao Lin 004; Sebastian U. Stich; Kumar Kshitij Patel; Martin Jaggi (ICLR, 2020)

Extrapolation for Large-batch Training in Deep Learning. - Tao Lin 004; Lingjing Kong 001; Sebastian U. Stich; Martin Jaggi (ICML, 2020)

Ensemble Distillation for Robust Model Fusion in Federated Learning. - Tao Lin 004; Lingjing Kong 001; Sebastian U. Stich; Martin Jaggi (NeurIPS, 2020)

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them. - Chen Liu 027; Mathieu Salzmann; Tao Lin 004; Ryota Tomioka; Sabine Süsstrunk (NeurIPS, 2020)

Masking as an Efficient Alternative to Finetuning for Pretrained Language Models. - Mengjie Zhao; Tao Lin 004; Martin Jaggi; Hinrich Schütze (CoRR, 2020)

GA-Par: Dependable Microservice Orchestration Framework for Geo-Distributed Clouds. - Zhenyu Wen; Tao Lin 004; Renyu Yang; Shouling Ji; Rajiv Ranjan 001; Alexander B. Romanovsky; Chang-Ting Lin; Jie Xu 007 (IEEE Trans. Parallel Distributed Syst., 2020)

Consensus Control for Decentralized Deep Learning. - Lingjing Kong 001; Tao Lin 004; Anastasia Koloskova; Martin Jaggi; Sebastian U. Stich (ICML, 2021)

Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data. - Tao Lin 004; Sai Praneeth Karimireddy; Sebastian U. Stich; Martin Jaggi (ICML, 2021)

An Improved Analysis of Gradient Tracking for Decentralized Machine Learning. - Anastasia Koloskova; Tao Lin 004; Sebastian U. Stich (NeurIPS, 2021)

RelaySum for Decentralized Deep Learning on Heterogeneous Data. - Thijs Vogels; Lie He; Anastasia Koloskova; Sai Praneeth Karimireddy; Tao Lin 004; Sebastian U. Stich; Martin Jaggi (NeurIPS, 2021)

Representation Memorization for Fast Learning New Knowledge without Forgetting. - Fei Mi; Tao Lin 004; Boi Faltings (CoRR, 2021)

Understanding Memorization from the Perspective of Optimization via Efficient Influence Estimation. - Futong Liu; Tao Lin 004; Martin Jaggi (CoRR, 2021)

Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition. - Jie Su 001; Zhenyu Wen; Tao Lin 004; Yu Guan (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2022)

Algorithms for Efficient and Robust Distributed Deep Learning. - Tao Lin 004 (2022)

Decentralized Gradient Tracking with Local Steps. - Yue Liu; Tao Lin 004; Anastasia Koloskova; Sebastian U. Stich (CoRR, 2023)

PathMMU: A Massive Multimodal Expert-Level Benchmark for Understanding and Reasoning in Pathology. - Yuxuan Sun 002; Hao Wu 072; Chenglu Zhu; Sunyi Zheng; Qizi Chen; Kai Zhang 033; Yunlong Zhang; Dan Wan; Xiaoxiao Lan; Mengyue Zheng; Jingxiong Li; Xinheng Lyu; et al. (ECCV (62), 2024)

PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration. - Yuxuan Sun 002; Yunlong Zhang; Yixuan Si; Chenglu Zhu; Zhongyi Shui; Kai Zhang 033; Jingxiong Li; Xingheng Lyu; Tao Lin 004; Lin Yang 002 (CoRR, 2024)

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology. - Yuxuan Sun 002; Yixuan Si; Chenglu Zhu; Xuan Gong; Kai Zhang 033; Pingyi Chen; Ye Zhang; Zhongyi Shui; Tao Lin 004; Lin Yang 002 (CVPR, 2025)

PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration. - Yuxuan Sun 002; Yunlong Zhang; Yixuan Si; Chenglu Zhu; Kai Zhang 033; Zhongyi Shui; Jingxiong Li; Xuan Gong; Xinheng Lyu; Tao Lin 004; Lin Yang 002 (ICLR, 2025)

CPathAgent: An Agent-based Foundation Model for Interpretable High-Resolution Pathology Image Analysis Mimicking Pathologists' Diagnostic Logic. - Yuxuan Sun 002; Yixuan Si; Chenglu Zhu; Kai Zhang 033; Zhongyi Shui; Bowen Ding; Tao Lin 004; Lin Yang 002 (CoRR, 2025)

Open Source AI-based SE Tools: Opportunities and Challenges of Collaborative Software Learning. - Zhihao Lin; Wei Ma; Tao Lin 004; Yaowen Zheng; Jingquan Ge; Jun Wang 020; Jacques Klein; Tegawendé F. Bissyandé; Yang Liu 003; Li Li 029 (ACM Trans. Softw. Eng. Methodol., 2025)