English(EN) TreeWalker: Partial Evaluation for Grouped Tree-Ensemble Inference

TreeWalker 加速分组数据的树集成推理

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-21 04:00

研究人员开发了 TreeWalker，这是一种新颖的推理技术，旨在加速处理分组相关数据行的树集成模型的处理。通过识别并将恒定特征视为静态，TreeWalker 通过划分变化特征和跳过不相关的子树来优化遍历。该方法与标准的 LightGBM 和 XGBoost 模型兼容，在 Intel 处理器上实现了高达 3 倍的性能提升，在 Arm 处理器上实现了高达 2.9 倍的性能提升，与中等规模分组的独立行方法相比，在更大分组规模下性能提升更大。 AI

影响加速了常见的树集成模型的推理，可能降低生存分析和点击率预测等应用的计算成本。

排序理由关于树集成模型新推理技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 关于树集成模型新推理技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, infra; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: 2 days old; Coverage has settled into its steady-state source set.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Durmus Karatay, Richard Newman · 2026-10-21 04:00

TreeWalker：分组树集成推理的局部求值

arXiv:2610.03939v2 Announce Type: replace Abstract: Many prediction tasks evaluate a trained tree ensemble on groups of rows that share feature values: discrete-time survival models expand each patient into $G$ time steps, click-through-rate models score every item in a search se…

本文如何被排名

报道来源 [1]

TreeWalker：分组树集成推理的局部求值

相关实体

相关话题