Tag: high-dimensional data

Researchers at the University of Calabria have developed RLAX, a reinforcement learning framework that identifies compact, interpretable feature subspaces explaining ...

Researchers adapted a swarm intelligence algorithm modeled on great white shark hunting behavior to select the most informative genes from ...

Researchers have developed ProD, a visualizable filter feature selection method that ranks variables by measuring the geometric overlap between class ...

Two Georgia State University doctoral students, Ahanab Hafiz Anab and Haobo Cui, are among only four recipients of the 2026 ...

Registration has opened for the SIAM Conference on Mathematics of Data Science, MDS26, which will convene researchers from academia, industry, ...

Chinese researchers have combined dynamic attribute clustering, TOPSIS and Borda count voting to turn high-dimensional tourist review data into reliable ...

A new three-stage algorithm called FS-GSR combines graph-based scoring with sparse reconstruction to select compact, high-performing feature subsets from high-dimensional ...

Researchers have unveiled a subspace clustering framework that preserves the structural fidelity of high-dimensional data while avoiding the prohibitive cost ...

A new deterministic heuristic called EPR-C3 recovers most of the best predictor subsets found by exhaustive regression while dramatically cutting ...

Researchers at Manipur University have developed EF²RB, an ensemble feature selection framework that boosts IoT intrusion detection accuracy to between ...