From d0f7b30b61c992a2ce00b332cfe484b339148e18 Mon Sep 17 00:00:00 2001 From: Qingyun Wu Date: Fri, 3 Feb 2023 16:57:16 -0800 Subject: [PATCH] update doc for research papers --- notebook/autovw.ipynb | 2 +- website/docs/Research.md | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/notebook/autovw.ipynb b/notebook/autovw.ipynb index 1d00d3d80..9292ad666 100644 --- a/notebook/autovw.ipynb +++ b/notebook/autovw.ipynb @@ -20,7 +20,7 @@ "\n", "In this notebook, we use one real data example (regression task) to showcase AutoVW, which is an online AutoML solution based on the following work:\n", "\n", - "*ChaCha for online AutoML. Qingyun Wu, Chi Wang, John Langford, Paul Mineiro and Marco Rossi. To appear in ICML 2021.*\n", + "*ChaCha for online AutoML. Qingyun Wu, Chi Wang, John Langford, Paul Mineiro and Marco Rossi. ICML 2021.*\n", "\n", "AutoVW is implemented in FLAML. FLAML requires `Python>=3.7`. To run this notebook example, please install:" ] diff --git a/website/docs/Research.md b/website/docs/Research.md index 6ed880d6f..07d942244 100644 --- a/website/docs/Research.md +++ b/website/docs/Research.md @@ -19,3 +19,4 @@ For technical details, please check our research publications. * [ChaCha for Online AutoML](https://www.microsoft.com/en-us/research/publication/chacha-for-online-automl/). Qingyun Wu, Chi Wang, John Langford, Paul Mineiro and Marco Rossi. ICML 2021. * [Fair AutoML](https://arxiv.org/abs/2111.06495). Qingyun Wu, Chi Wang. ArXiv preprint arXiv:2111.06495 (2021). * [Mining Robust Default Configurations for Resource-constrained AutoML](https://arxiv.org/abs/2202.09927). Moe Kayali, Chi Wang. ArXiv preprint arXiv:2202.09927 (2022). +* [Targeted Hyperparameter Optimization with Lexicographic Preferences Over Multiple Objectives](https://openreview.net/forum?id=0Ij9_q567Ma). Shaokun Zhang, Feiran Jia, Chi Wang, Qingyun Wu. ICLR 2023 (notable-top-5%).