Moving-horizon approximate branch-and-reduce method to train near-optimal deep classification trees on large-scale data
Read the original at arxiv.org→arXiv:2609.38194v1 Announce Type: new Abstract: Despite the importance for interpretability, decision trees face severe scalability challenges. Existing global optimal methods are often limited by binary feature...
Original headline: "A Moving-Horizon Approximate Branch-and-Reduce Method for Deep Classification Trees"
Coverage timeline
- Oct 1, 04:00 UTC arXiv cs.LG lead source A Moving-Horizon Approximate Branch-and-Reduce Method for Deep Classification Trees