Search Results for author:
Found 3 papers, 2 papers with code
Leaping Through Time with Gradient-based Adaptation for Recommendation
Different from the popular recurrent modeling approach, we propose a new solution named LeapRec to the temporal dynamic problem by using trajectory-based meta-learning to model time dependencies.
Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous Graph
To address this challenge, we propose dictionary-based heterogeneous graph neural network (DHGNet) that effectively handles the heterogeneity of DHG by two-step aggregations, which are word-level and language-level aggregations.
On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective
In this paper, we first prove that the focal loss is classification-calibrated, i. e., its minimizer surely yields the Bayes-optimal classifier and thus the use of the focal loss in classification can be theoretically justified.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
