Spectral analysis of tree ensembles produces minimax rates for random forests governed by kernel eigenvalue decay and enables distillation of RFs and GBMs into compact models via leading eigenfunctions and singular vectors.
citation dossier
Interpreting models via single tree approximation
2Pith papers citing it
2reference links
cs.LGtop field · 1 papers
UNVERDICTEDtop verdict bucket · 2 papers
why this work matters in Pith
Pith has found this work in 2 reviewed papers. Its strongest current cluster is cs.LG (1 papers). The largest review-status bucket among citing papers is UNVERDICTED (2 papers). For highly cited works, this page shows a dossier first and a bounded explorer second; it never tries to render every citing paper at once.
years
2026 2verdicts
UNVERDICTED 2representative citing papers
PACE interleaves active generation of diverse learners with subsequent pruning to produce smaller ensembles that retain performance and offer faithfulness guarantees.
citing papers explorer
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Minimax Rates and Spectral Distillation for Tree Ensembles
Spectral analysis of tree ensembles produces minimax rates for random forests governed by kernel eigenvalue decay and enables distillation of RFs and GBMs into compact models via leading eigenfunctions and singular vectors.
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PACE: Prune-And-Compress Ensemble Models
PACE interleaves active generation of diverse learners with subsequent pruning to produce smaller ensembles that retain performance and offer faithfulness guarantees.