Blocked 3×2 Cross-Validated t-Test for Comparing Supervised Classification Learning Algorithms. - Yu Wang 092; Ruibo Wang; Huichen Jia; Jihong Li (Neural Comput., 2014)

Measure for data partitioning in m × 2 cross-validation. - Yu Wang 092; Jihong Li; Yanfang Li (Pattern Recognit. Lett., 2015)

Confidence Interval for F1 Measure of Algorithm Performance Based on Blocked 3× 2 Cross-Validation. - Yu Wang 092; Jihong Li; Yanfang Li; Ruibo Wang; Xingli Yang (IEEE Trans. Knowl. Data Eng., 2015)

Unbiased condition of the dispersion effects estimator in unreplicated two-level factorial experiments. - Yang Liu; Jihong Li; Yu Wang 092 (J. Syst. Sci. Complex., 2016)

Credible Intervals for Precision and Recall Based on a K-Fold Cross-Validated Beta Distribution. - Yu Wang 092; Jihong Li (Neural Comput., 2016)

Block-Regularized m × 2 Cross-Validated Estimator of the Generalization Error. - Ruibo Wang; Yu Wang 092; Jihong Li; Xingli Yang; Jing Yang (Neural Comput., 2017)

Choosing Between Two Classification Learning Algorithms Based on Calibrated Balanced 5 × 2 Cross-Validated F-Test. - Yu Wang 092; Jihong Li; Yanfang Li (Neural Process. Lett., 2017)

Calibrating GloVe model on the principle of Zipf's law. - Xuefei Cao; Jihong Li; Ruibo Wang; Yu Wang 092; Qian Niu; Junfeng Shi (Pattern Recognit. Lett., 2019)

Tuning Parameter Selection Based on Blocked 3˟ 2 Cross-Validation for High-Dimensional Linear Regression Model. - Xingli Yang; Yu Wang 092; Ruibo Wang; Mengmeng Chen; Jihong Li (Neural Process. Lett., 2020)

We Need to Talk About Reproducibility in NLP Model Comparison. - Yan Xue; Xuefei Cao; Xingli Yang; Yu Wang 092; Ruibo Wang; Jihong Li (EMNLP, 2023)