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Bellman Meets Hawkes: Model-Based Reinforcement Learning via Temporal Point Processes



Chao Qu , Xiaoyu Tan , Siqiao Xue , Xiaoming Shi , James Zhang , Hongyuan Mei


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Transformer Embeddings of Irregularly Spaced Events and Their Participants



Chenghao Yang , Hongyuan Mei , Jason Eisner


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Noise-Contrastive Estimation for Multivariate Point Processes



Hongyuan Mei , Tom Wan , Jason Eisner

* NeurIPS 2020 camera-ready 

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Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification



Hongyuan Mei , Guanghui Qin , Minjie Xu , Jason Eisner

* ICML 2020 (near-camera-ready version) 

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Imputing Missing Events in Continuous-Time Event Streams



Hongyuan Mei , Guanghui Qin , Jason Eisner

* ICML 2019 camera-ready. The first version of this work appeared on OpenReview in September 2018 

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On the Idiosyncrasies of the Mandarin Chinese Classifier System



Shijia Liu , Hongyuan Mei , Adina Williams , Ryan Cotterell


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Halo: Learning Semantics-Aware Representations for Cross-Lingual Information Extraction



Hongyuan Mei , Sheng Zhang , Kevin Duh , Benjamin Van Durme

* *SEM 2018 camera-ready 

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The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process



Hongyuan Mei , Jason Eisner

* NIPS 2017 camera-ready. New experiments including intensity prediction evaluation, sensitivity to # of parameters, training speed analysis. Results updated to use final test data instead of devtest. Improved exposition, especially of continuous-time LSTM and thinning algorithm 

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Coherent Dialogue with Attention-based Language Models



Hongyuan Mei , Mohit Bansal , Matthew R. Walter

* To appear at AAAI 2017 

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What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment



Hongyuan Mei , Mohit Bansal , Matthew R. Walter


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