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Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment
Chenxiao Yang · Qitian Wu · Qingsong Wen · Zhiqiang Zhou · Liang Sun · Junchi Yan

Tue Nov 29 02:00 PM -- 04:00 PM (PST) @ Hall J #223

The goal of sequential event prediction is to estimate the next event based on a sequence of historical events, with applications to sequential recommendation, user behavior analysis and clinical treatment. In practice, the next-event prediction models are trained with sequential data collected at one time and need to generalize to newly arrived sequences in remote future, which requires models to handle temporal distribution shift from training to testing. In this paper, we first take a data-generating perspective to reveal a negative result that existing approaches with maximum likelihood estimation would fail for distribution shift due to the latent context confounder, i.e., the common cause for the historical events and the next event. Then we devise a new learning objective based on backdoor adjustment and further harness variational inference to make it tractable for sequence learning problems. On top of that, we propose a framework with hierarchical branching structures for learning context-specific representations. Comprehensive experiments on diverse tasks (e.g., sequential recommendation) demonstrate the effectiveness, applicability and scalability of our method with various off-the-shelf models as backbones.

Author Information

Chenxiao Yang (Shanghai Jiao Tong University)
Qitian Wu (Shanghai Jiao Tong University)
Qingsong Wen (Alibaba Group U.S. Inc.)

Dr. Qingsong Wen is a Staff Engineer / Team Leader at DAMO Academy-Decision Intelligence Lab, Alibaba Group (U.S.), working in the areas of intelligent time series analysis, data-driven intelligence decisions, machine learning, and signal processing. He received his M.S. and Ph.D. degrees in Electrical and Computer Engineering from Georgia Institute of Technology, Atlanta, USA. He has published over 40 top-ranked conference and journal papers, and won First Place in the 2022 ICASSP Grand Challenge (AIOps in Networks) Competition. He is an Associate Editor for Neurocomputing, Guest Editor for Pattern Recognition, Guest Editor for Applied Energy, and regularly served as an SPC/PC member of the major DM/ML/AI conferences including KDD, ICDM, AAAI, IJCAI, etc.

Zhiqiang Zhou
Liang Sun (Alibaba Group)
Junchi Yan (Shanghai Jiao Tong University)

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