most citedDeep-Wide Learning Assistance for Insect Pest Classification

4 citations · 5 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2025

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…

cs.LG2025

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.…

cs.LG2025

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…

cs.LG2025

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…

cs.LG2025

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…

cs.CV2024★ 4 cited

Deep-Wide Learning Assistance for Insect Pest Classification

Toan Nguyen, Huy Nguyen, Huy Ung +2

Accurate insect pest recognition plays a critical role in agriculture. It is a challenging problem due to the intricate characteristics of insects. In this paper, we present DeWi,…

cs.LG2024★ 1 cited

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…