The authors of the research presented at AISTATS 2026 provide theoretical guarantees for early stopping of kernel-based methods for neural networks with sufficiently large width and gradient-boosting decision trees that use symmetric trees as weak learners.

Authors

• Person: Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche Organization: AISTATS
  Track: Poster Session 3 - aistats 2026

Sources

• Track: Poster Session 3 - aistats 2026 virtual.aistats.org Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche · AISTATS via serper

Referenced by nodes (1)

• artificial neural networks concept