Tackling Diverse Minorities in Imbalanced Classification

no code implementations • 28 Aug 2023 • Kwei-Herng Lai, Daochen Zha, Huiyuan Chen, Mangesh Bendre, Yuzhong Chen, Mahashweta Das, Hao Yang, Xia Hu

Imbalanced datasets are commonly observed in various real-world applications, presenting significant challenges in training classifiers.

Anomaly Detection Classification +2

Few-shot graph link prediction with domain adaptation

no code implementations • 29 Sep 2021 • Hao Zhu, Mahashweta Das, Mangesh Bendre, Fei Wang, Hao Yang, Soha Hassoun

In this work, we propose an adversarial training based modification to the current state-of-the-arts link prediction method to solve this problem.

Domain Adaptation Few-Shot Learning +1

Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation

no code implementations • 21 May 2020 • Adit Krishnan, Mahashweta Das, Mangesh Bendre, Hao Yang, Hari Sundaram

The rapid proliferation of new users and items on the social web has aggravated the gray-sheep user/long-tail item challenge in recommender systems.

Clustering Collaborative Filtering +2