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DimBoost: Boosting Gradient Boosting Decision Tree to Higher Dimensions

Summary: DimBoost is a scalable GBDT trainer for ultra-high dimensional data (330K features), with a performance model revealing collective-communication bottlenecks. Key innovations: scheduler, two-phase split finding, sparsity-aware histograms with parallel indexing, and low-precision gradients; 2–9x speedups over existing systems. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5538
Venue
SIGMOD
Year
2018
Pagerank
4.3342363e-05
Overall Rank
9,469 | 34.13%
DOI
10.1145/3183713.3196892

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