4 citations · 5 across the 6 of their papers we have counts for
6 papers · 1 filter
Wasserstein Robust Classification Error: Surrogate Loss Misalignment and Distributional Attacks
Bach C. Le, Tung V. Dao, Binh T. Nguyen +1
Wasserstein distributionally robust optimization (WDRO) provides a framework for evaluating model robustness through the worst-case expectation in the Wasserstein ball around a ref…
Large Language Models for Imbalanced Classification: Diversity makes the difference
Dang Nguyen, Sunil Gupta, Kien Do +4
Oversampling is one of the most widely used approaches for addressing imbalanced classification. The core idea is to generate additional minority samples to rebalance the dataset.…
Missing Data Imputation using Neural Cellular Automata
Tin Luu, Binh Nguyen, Man Ngo
When working with tabular data, missingness is always one of the most painful problems. Throughout many years, researchers have continuously explored better and better ways to impu…
HFedATM: Hierarchical Federated Domain Generalization via Optimal Transport and Regularized Mean Aggregation
Thinh Nguyen, Trung Phan, Binh T. Nguyen +2
Federated Learning (FL) is a decentralized approach where multiple clients collaboratively train a shared global model without sharing their raw data. Despite its effectiveness, co…
Sequence Transferability and Task Order Selection in Continual Learning
Thinh Nguyen, Cuong N. Nguyen, Quang Pham +4
In continual learning, understanding the properties of task sequences and their relationships to model performance is important for developing advanced algorithms with better accur…
Overcoming Catastrophic Forgetting in Federated Class-Incremental Learning via Federated Global Twin Generator
Thinh Nguyen, Khoa D Doan, Binh T. Nguyen +2
Federated Class-Incremental Learning (FCIL) increasingly becomes important in the decentralized setting, where it enables multiple participants to collaboratively train a global mo…