1 citations · 1 across the 3 of their papers we have counts for
5 papers
Sparse Orthogonal Regression Technique: A Spectral Framework for Equation Discovery, Approximation, and Integration
Sabin Roman, Ljupco Todorovski, Saso Dzeroski
We develop the Sparse Orthogonal Regression Technique (SORT), a sparse spectral framework for learning orthonormal-basis expansions from noisy and irregularly sampled data. SORT es…
Limits of spectral learning under noise
Sabin Roman, Ljupco Todorovski, Saso Dzeroski +2
Learning functional relationships from noisy data is a central problem in scientific inference. Spectral methods approximate unknown functions by expanding them in a basis and esti…
Approximating the universal thermal climate index using sparse regression with orthogonal polynomials
Sabin Roman, Ljupco Todorovski, Saso Dzeroski +1
The Universal Thermal Climate Index (UTCI) is a measure of thermal comfort that quantifies how humans experience environmental conditions. Due to its robustness and versatility as…
Predicting Hidden Links and Missing Nodes in Scale-Free Networks with Artificial Neural Networks
Rakib Hassan Pran
There are many networks in real life which exist as form of Scale-free networks such as World Wide Web, protein-protein interaction network, semantic networks, airline networks, in…
Combining Textual and Structural Information for Premise Selection in Lean
Job PetrovÄiÄ, David Eliecer Narvaez Denis, LjupÄo Todorovski
Premise selection is a key bottleneck for scaling theorem proving in large formal libraries. Yet existing language-based methods often treat premises in isolation, ignoring the web…