most citedBenchmarking state-of-the-art gradient boosting algorithms for classification

15 citations · 15 across the 2 of their papers we have counts for

collaborators

2 papers

cs.DC2026

Meeting SLOs, Slashing Hours: Automated Enterprise LLM Optimization with OptiKIT

Nicholas Santavas, Kareem Eissa, Patrycja Cieplicka +6

Enterprise LLM deployment faces a critical scalability challenge: organizations must optimize models systematically to scale AI initiatives within constrained compute budgets, yet…

cs.LG2023★ 15 cited

Benchmarking state-of-the-art gradient boosting algorithms for classification

Piotr Florek, Adam Zagdański

This work explores the use of gradient boosting in the context of classification. Four popular implementations, including original GBM algorithm and selected state-of-the-art gradi…