From d123bcabdf76d4a2b361696791e1e8f5b398fe74 Mon Sep 17 00:00:00 2001 From: James Lamb Date: Sun, 11 Jun 2023 23:04:55 -0500 Subject: [PATCH 1/3] [docs] add quantized training paper to docs --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index e63e0a0ecf7d..55c85e38d21d 100644 --- a/README.md +++ b/README.md @@ -145,6 +145,8 @@ This project has adopted the [Microsoft Open Source Code of Conduct](https://ope Reference Papers ---------------- +Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu. "Quantized Training of Gradient Boosting Decision Trees" ([link](https://papers.nips.cc/paper_files/paper/2022/file/77911ed9e6e864ca1a3d165b2c3cb258-Paper-Conference.pdf)). Advances in Neural Information Processing Systems 35 (NeurIPS 2022), pp. 18822-18833. + Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu. "[LightGBM: A Highly Efficient Gradient Boosting Decision Tree](https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree)". Advances in Neural Information Processing Systems 30 (NIPS 2017), pp. 3149-3157. Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Tie-Yan Liu. "[A Communication-Efficient Parallel Algorithm for Decision Tree](http://papers.nips.cc/paper/6380-a-communication-efficient-parallel-algorithm-for-decision-tree)". Advances in Neural Information Processing Systems 29 (NIPS 2016), pp. 1279-1287. From ef143b595124c84e148955304da342d5b42397b1 Mon Sep 17 00:00:00 2001 From: James Lamb Date: Mon, 12 Jun 2023 09:51:08 -0500 Subject: [PATCH 2/3] empty commit From 6e5975864d07f6265fad2f10ac1646ca26f44909 Mon Sep 17 00:00:00 2001 From: James Lamb Date: Wed, 14 Jun 2023 15:14:13 -0500 Subject: [PATCH 3/3] link to abstract --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 55c85e38d21d..a44d557f058b 100644 --- a/README.md +++ b/README.md @@ -145,7 +145,7 @@ This project has adopted the [Microsoft Open Source Code of Conduct](https://ope Reference Papers ---------------- -Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu. "Quantized Training of Gradient Boosting Decision Trees" ([link](https://papers.nips.cc/paper_files/paper/2022/file/77911ed9e6e864ca1a3d165b2c3cb258-Paper-Conference.pdf)). Advances in Neural Information Processing Systems 35 (NeurIPS 2022), pp. 18822-18833. +Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu. "Quantized Training of Gradient Boosting Decision Trees" ([link](https://papers.nips.cc/paper_files/paper/2022/hash/77911ed9e6e864ca1a3d165b2c3cb258-Abstract.html)). Advances in Neural Information Processing Systems 35 (NeurIPS 2022), pp. 18822-18833. Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu. "[LightGBM: A Highly Efficient Gradient Boosting Decision Tree](https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree)". Advances in Neural Information Processing Systems 30 (NIPS 2017), pp. 3149-3157.