168 citations · 169 across the 4 of their papers we have counts for
5 papers
Compact set-valued deep ensembling in multi-class classification
Kim-Dung Tran, Dang-Man Nguyen, Vu-Linh Nguyen +3
This paper tackles visible challenges in deep ensemble learning, where deep neural networks serve as ensemble members: training and storage burdens, and robustness of cautious (set…
GaussianPSL: Soft partitioning for complex PSL problem
Phuong Mai Dinh, Van-Nam Huynh
Many practical applications of multi-objective optimization (MOO), including engineering design, autonomous systems, and machine learning, often yield complex Pareto frontiers (e.g…
Synergistic Fusion of Multi-Source Knowledge via Evidence Theory for High-Entropy Alloy Discovery
Minh-Quyet Ha, Dinh-Khiet Le, Duc-Anh Dao +6
Discovering novel high-entropy alloys (HEAs) with desirable properties is challenging due to the vast compositional space and complex phase formation mechanisms. Efficient explorat…
Estimating the Optimal Number of Clusters in Categorical Data Clustering by Silhouette Coefficient
Duy-Tai Dinh, Tsutomu Fujinami, Van-Nam Huynh
The problem of estimating the number of clusters (say k) is one of the major challenges for the partitional clustering. This paper proposes an algorithm named k-SCC to estimate the…
Categorical data clustering: 25 years beyond K-modes
Tai Dinh, Wong Hauchi, Philippe Fournier-Viger +4
The clustering of categorical data is a common and important task in computer science, offering profound implications across a spectrum of applications. Unlike purely numerical dat…