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LogAI: A Library for Log Analytics and Intelligence


Jan 31, 2023
Qian Cheng, Amrita Saha, Wenzhuo Yang, Chenghao Liu, Doyen Sahoo, Steven Hoi

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* 17 pages, 7 figures, technical report for open source code, paper release with code 

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Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data


Jan 25, 2023
Devansh Arpit, Matthew Fernandez, Chenghao Liu, Weiran Yao, Wenzhuo Yang, Paul Josel, Shelby Heinecke, Eric Hu, Huan Wang, Stephen Hoi, Caiming Xiong, Kun Zhang, Juan Carlos Niebles

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Continual Learning: Fast and Slow


Sep 06, 2022
Quang Pham, Chenghao Liu, Steven C. H. Hoi

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* arXiv admin note: substantial text overlap with arXiv:2110.00175 

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DeepTIMe: Deep Time-Index Meta-Learning for Non-Stationary Time-Series Forecasting


Jul 14, 2022
Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi

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Scalar is Not Enough: Vectorization-based Unbiased Learning to Rank


Jun 03, 2022
Mouxiang Chen, Chenghao Liu, Zemin Liu, Jianling Sun

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* Accepted by KDD 2022 

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Continual Normalization: Rethinking Batch Normalization for Online Continual Learning


Mar 30, 2022
Quang Pham, Chenghao Liu, Steven Hoi

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* International Conference on Learning Representations, 2022 

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Learning Fast and Slow for Online Time Series Forecasting


Feb 23, 2022
Quang Pham, Chenghao Liu, Doyen Sahoo, Steven C. H. Hoi

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CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting


Feb 03, 2022
Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi

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ETSformer: Exponential Smoothing Transformers for Time-series Forecasting


Feb 03, 2022
Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi

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Node-wise Localization of Graph Neural Networks


Oct 27, 2021
Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi

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* Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI 2021) 

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