mirror of
				https://github.com/microsoft/autogen.git
				synced 2025-10-31 09:50:11 +00:00 
			
		
		
		
	update doc for research papers
This commit is contained in:
		
							parent
							
								
									50a7b624d1
								
							
						
					
					
						commit
						d0f7b30b61
					
				| @ -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:" | ||||
|    ] | ||||
|  | ||||
| @ -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%). | ||||
|  | ||||
		Loading…
	
	
			
			x
			
			
		
	
		Reference in New Issue
	
	Block a user
	 Qingyun Wu
						Qingyun Wu