Tsuyoshi Murata — accepted AI-conference papers

2022

Leaping through Time with Gradient-Based Adaptation for Recommendation

Nuttapong Chairatanakul, Hoang NT, Xin Liu, Tsuyoshi Murata

AAAI 2022technical

Modern recommender systems are required to adapt to the change in user preferences and item popularity. Such a problem is known as the temporal dynamics problem, and it is one of the main challenges in recommender system modeling. Different from the popular recurrent modeling approach, we propose a…

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2021

Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous Graph

Nuttapong Chairatanakul, Noppayut Sriwatanasakdi, Nontawat Charoenphakdee, Xin Liu, Tsuyoshi Murata

EMNLP 2021finding

In cross-lingual text classification, it is required that task-specific training data in high-resource source languages are available, where the task is identical to that of a low-resource target language. However, collecting such training data can be infeasible because of the labeling cost, task ch…

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