Experimental Results

doi:doi:10.57702/m8kruj4z

Experimental Results

The authors evaluate the performance of their proposed conformal prediction methods for multistep feedback covariate shift (MFCS) on synthetic black-box optimization and active learning tasks.

BibTex:

@dataset{Yuchen_Cai_and_Ding_Cao_and_Rongxi_Guo_and_Yaqin_Wen_and_Guiquan_Liu_and_Enhong_Chen_2024,
    abstract = {The authors evaluate the performance of their proposed conformal prediction methods for multistep feedback covariate shift (MFCS) on synthetic black-box optimization and active learning tasks.},
    author = {Yuchen Cai and Ding Cao and Rongxi Guo and Yaqin Wen and Guiquan Liu and Enhong Chen},
    doi = {10.57702/m8kruj4z},
    institution = {No Organization},
    keyword = {'3-SAT', 'Active learning', 'Black-box optimization', 'Boolean Satisfiability Problem', 'CBLUE', 'CLUE', 'COPA', 'CommonsenseQA', 'Conformal prediction', 'GLUE', 'HellaSwag', 'Heuristic Algorithms', 'LAMBADA', 'Professions Dataset', 'Protein design', 'RTE', 'Text Classification', 'WinoBias', 'WinoGender', 'bus scheduling', 'experimental results'},
    month = {dec},
    publisher = {TIB},
    title = {Experimental Results},
    url = {https://service.tib.eu/ldmservice/dataset/experimental-results},
    year = {2024}
}