5 citations · 5 across the 4 of their papers we have counts for
4 papers
Anomaly Detection via Mean Shift Density Enhancement
Pritam Kar, Rahul Bordoloi, Olaf Wolkenhauer +1
Unsupervised anomaly detection stands as an important problem in machine learning. Existing unsupervised anomaly detection algorithms rarely perform well across different anomaly t…
FUSE: Fast Semi-Supervised Node Embedding Learning via Structural and Label-Aware Optimization
Sujan Chakraborty, Rahul Bordoloi, Anindya Sengupta +2
Graph-based learning is a cornerstone for analyzing structured data, with node classification as a central task. However, in many real-world graphs, nodes lack informative feature…
Handling Missing Data in Downstream Tasks With Distribution-Preserving Guarantees
Rahul Bordoloi, Clémence Réda, Saptarshi Bej +1
Missing feature values are a significant hurdle for downstream machine-learning tasks such as classification. However, imputation methods for classification might be time-consuming…
Multivariate Functional Linear Discriminant Analysis for the Classification of Short Time Series with Missing Data
Rahul Bordoloi, Clémence Réda, Orell Trautmann +2
Functional linear discriminant analysis (FLDA) is a powerful tool that extends LDA-mediated multiclass classification and dimension reduction to univariate time-series functions. H…