24 citations · 52 across the 11 of their papers we have counts for
28 papers
Unsupervised Learning for Identifying High Eigenvector Centrality Nodes: A Graph Neural Network Approach
Appan Rakaraddi, Mahardhika Pratama
The existing methods to calculate the Eigenvector Centrality(EC) tend to not be robust enough for determination of EC in low time complexity or not well-scalable for large networks…
ACDC: Online Unsupervised Cross-Domain Adaptation
Marcus de Carvalho, Mahardhika Pratama, Jie Zhang +1
We consider the problem of online unsupervised cross-domain adaptation, where two independent but related data streams with different feature spaces -- a fully labeled source strea…
Unsupervised Continual Learning in Streaming Environments
Andri Ashfahani, Mahardhika Pratama
A deep clustering network is desired for data streams because of its aptitude in extracting natural features thus bypassing the laborious feature engineering step. While automatic…
Automatic Online Multi-Source Domain Adaptation
Renchunzi Xie, Mahardhika Pratama
Knowledge transfer across several streaming processes remain challenging problem not only because of different distributions of each stream but also because of rapidly changing and…
Unsupervised Continual Learning via Self-Adaptive Deep Clustering Approach
Mahardhika Pratama, Andri Ashfahani, Edwin Lughofer
Unsupervised continual learning remains a relatively uncharted territory in the existing literature because the vast majority of existing works call for unlimited access of ground…
Scalable Teacher Forcing Network for Semi-Supervised Large Scale Data Streams
Mahardhika Pratama, Choiru Za'in, Edwin Lughofer +2
The large-scale data stream problem refers to high-speed information flow which cannot be processed in scalable manner under a traditional computing platform. This problem also imp…