3 papers
cs.LG2026
Data Enrichment for Symbolic Regression Using Diffusion Models
Simon De Reuver, Tamas Kristof Toth, Teddy Lazebnik
Symbolic regression (SR) offers a route to scientific discovery by converting observations into interpretable governing equations. However, despite its promise, its reliability deg…
cs.LG2026
Profiling Privacy Preservation Against Gradient Inversion Attacks in Tabular Federated Learning
Ivo Osterberg Nilsson, Maximilian Birr Engvall, Viktor Valadi +1
Federated learning (FL) enables multiple data holders to train machine learning models collaboratively without centralizing raw data, making it useful in privacy sensitive domains…
cs.LG2026
Quality-preserving Model for Electronics Production Quality Tests Reduction
Noufa Haneefa, Teddy Lazebnik, Einav Peretz-Andersson
Manufacturing test flows in high-volume electronics production are typically fixed during product development and executed unchanged on every unit, even as failure patterns and pro…