Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances. - Marthinus Christoffel du Plessis; Gang Niu 001; Masashi Sugiyama (TAAI, 2013)

Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances - Marthinus Christoffel du Plessis; Masashi Sugiyama (CoRR, 2013)

Direct Divergence Approximation between Probability Distributions and Its Applications in Machine Learning. - Masashi Sugiyama; Song Liu 002; Marthinus Christoffel du Plessis; Masao Yamanaka; Makoto Yamada; Taiji Suzuki; Takafumi Kanamori (J. Comput. Sci. Eng., 2013)

Density-Difference Estimation. - Masashi Sugiyama; Takafumi Kanamori; Taiji Suzuki; Marthinus Christoffel du Plessis; Song Liu 002; Ichiro Takeuchi (Neural Comput., 2013)

Transductive Learning with Multi-class Volume Approximation. - Gang Niu 001; Bo Dai 001; Marthinus Christoffel du Plessis; Masashi Sugiyama (ICML, 2014)

Analysis of Learning from Positive and Unlabeled Data. - Marthinus Christoffel du Plessis; Gang Niu 001; Masashi Sugiyama (NIPS, 2014)

Constrained Least-Squares Density-Difference Estimation. - Tuan Duong Nguyen; Marthinus Christoffel du Plessis; Takafumi Kanamori; Masashi Sugiyama (IEICE Trans. Inf. Syst., 2014)

Class Prior Estimation from Positive and Unlabeled Data. - Marthinus Christoffel du Plessis; Masashi Sugiyama (IEICE Trans. Inf. Syst., 2014)

Semi-supervised learning of class balance under class-prior change by distribution matching. - Marthinus Christoffel du Plessis; Masashi Sugiyama (Neural Networks, 2014)

Continuous Target Shift Adaptation in Supervised Learning. - Tuan Duong Nguyen; Marthinus Christoffel du Plessis; Masashi Sugiyama (ACML, 2015)

Convex Formulation for Learning from Positive and Unlabeled Data. - Marthinus Christoffel du Plessis; Gang Niu 001; Masashi Sugiyama (ICML, 2015)

Online Direct Density-Ratio Estimation Applied to Inlier-Based Outlier Detection. - Marthinus Christoffel du Plessis; Hiroaki Shiino; Masashi Sugiyama (Neural Comput., 2015)

Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning. - Gang Niu 001; Marthinus Christoffel du Plessis; Tomoya Sakai 001; Yao Ma; Masashi Sugiyama (NIPS, 2016)

Theoretical Comparisons of Learning from Positive-Negative, Positive-Unlabeled, and Negative-Unlabeled Data. - Gang Niu 001; Marthinus Christoffel du Plessis; Tomoya Sakai 001; Masashi Sugiyama (CoRR, 2016)

Beyond the Low-density Separation Principle: A Novel Approach to Semi-supervised Learning. - Tomoya Sakai 001; Marthinus Christoffel du Plessis; Gang Niu 001; Masashi Sugiyama (CoRR, 2016)

Computationally Efficient Class-Prior Estimation under Class Balance Change Using Energy Distance. - Hideko Kawakubo; Marthinus Christoffel du Plessis; Masashi Sugiyama (IEICE Trans. Inf. Syst., 2016)

Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data. - Tomoya Sakai 001; Marthinus Christoffel du Plessis; Gang Niu 001; Masashi Sugiyama (ICML, 2017)

Positive-Unlabeled Learning with Non-Negative Risk Estimator. - Ryuichi Kiryo; Gang Niu 001; Marthinus Christoffel du Plessis; Masashi Sugiyama (NIPS, 2017)

Class-prior estimation for learning from positive and unlabeled data. - Marthinus Christoffel du Plessis; Gang Niu 001; Masashi Sugiyama (Mach. Learn., 2017)

Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. - Yung-Kyun Noh; Masashi Sugiyama; Song Liu 002; Marthinus Christoffel du Plessis; Frank Chongwoo Park; Daniel D. Lee (Neural Comput., 2018)