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Baoliang Cui

2 accepted papers

2023

Good Meta-tasks Make A Better Cross-lingual Meta-transfer Learning for Low-resource Languages

EMNLP 2023long findings

Model-agnostic meta-learning has garnered attention as a promising technique for enhancing few-shot cross-lingual transfer learning in low-resource scenarios. However, little attention was paid to the impact of data selection strategies on this cross-lingual meta-transfer method, particularly the sa…

Cited by 0SourceScholar
2021

Deep Wasserstein Graph Discriminant Learning for Graph Classification

AAAI 2021technical

Graph topological structures are crucial to distinguish different-class graphs. In this work, we propose a deep Wasserstein graph discriminant learning (WGDL) framework to learn discriminative embeddings of graphs in Wasserstein-metric (W-metric) matching space. In order to bypass the calculation of…

Cited by 19SourcePDFScholar