Marthinus Christoffel du Plessis

29 papers A* 4A 1C 2Journal 17Unranked 5

Year	Rank	Type	Title / Venue / Authors
2018	J	`jnl`	Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. Neural Comput. Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee
2017	J	`jnl`	Class-prior estimation for learning from positive and unlabeled data. Mach. Learn. Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama
2017	—	`conf`	Positive-Unlabeled Learning with Non-Negative Risk Estimator. NIPS Ryuichi Kiryo, Gang Niu, Marthinus Christoffel du Plessis, Masashi Sugiyama
2017	J	`jnl`	Positive-Unlabeled Learning with Non-Negative Risk Estimator. CoRR Ryuichi Kiryo, Gang Niu, Marthinus Christoffel du Plessis, Masashi Sugiyama
2017	A*	`conf`	Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data. ICML Tomoya Sakai, Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama
2016	J	`jnl`	Beyond the Low-density Separation Principle: A Novel Approach to Semi-supervised Learning. CoRR Tomoya Sakai, Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama
2016	J	`jnl`	Class-prior Estimation for Learning from Positive and Unlabeled Data. CoRR Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama
2016	J	`jnl`	Computationally Efficient Class-Prior Estimation under Class Balance Change Using Energy Distance. IEICE Trans. Inf. Syst. Hideko Kawakubo, Marthinus Christoffel du Plessis, Masashi Sugiyama
2016	J	`jnl`	Theoretical Comparisons of Learning from Positive-Negative, Positive-Unlabeled, and Negative-Unlabeled Data. CoRR Gang Niu, Marthinus Christoffel du Plessis, Tomoya Sakai, Masashi Sugiyama
2016	—	`conf`	Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning. NIPS Gang Niu, Marthinus Christoffel du Plessis, Tomoya Sakai, Yao Ma, Masashi Sugiyama
2015	C	`conf`	Class-prior Estimation for Learning from Positive and Unlabeled Data. ACML Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama
2015	C	`conf`	Continuous Target Shift Adaptation in Supervised Learning. ACML Tuan Duong Nguyen, Marthinus Christoffel du Plessis, Masashi Sugiyama
2015	A*	`conf`	Convex Formulation for Learning from Positive and Unlabeled Data. ICML Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama
2015	J	`jnl`	Online Direct Density-Ratio Estimation Applied to Inlier-Based Outlier Detection. Neural Comput. Marthinus Christoffel du Plessis, Hiroaki Shiino, Masashi Sugiyama
2014	—	`conf`	Analysis of Learning from Positive and Unlabeled Data. NIPS Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama
2014	A	`conf`	Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. AISTATS Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee
2014	J	`jnl`	Class Prior Estimation from Positive and Unlabeled Data. IEICE Trans. Inf. Syst. Marthinus Christoffel du Plessis, Masashi Sugiyama
2014	J	`jnl`	Constrained Least-Squares Density-Difference Estimation. IEICE Trans. Inf. Syst. Tuan Duong Nguyen, Marthinus Christoffel du Plessis, Takafumi Kanamori, Masashi Sugiyama
2014	J	`jnl`	Semi-supervised learning of class balance under class-prior change by distribution matching. Neural Networks Marthinus Christoffel du Plessis, Masashi Sugiyama
2014	A*	`conf`	Transductive Learning with Multi-class Volume Approximation. ICML Gang Niu, Bo Dai, Marthinus Christoffel du Plessis, Masashi Sugiyama
2014	J	`jnl`	Transductive Learning with Multi-class Volume Approximation. CoRR Gang Niu, Bo Dai, Marthinus Christoffel du Plessis, Masashi Sugiyama
2013	J	`jnl`	Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances CoRR Marthinus Christoffel du Plessis, Masashi Sugiyama
2013	—	`conf`	Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances. TAAI Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama
2013	J	`jnl`	Density-Difference Estimation. Neural Comput. Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi
2013	J	`jnl`	Direct Divergence Approximation between Probability Distributions and Its Applications in Machine Learning. J. Comput. Sci. Eng. Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Masao Yamanaka, Makoto Yamada, Taiji Suzuki, Takafumi Kanamori
2012	J	`jnl`	Density-Difference Estimation CoRR Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi
2012	—	`conf`	Density-Difference Estimation. NIPS Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi
2012	J	`jnl`	Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching CoRR Marthinus Christoffel du Plessis, Masashi Sugiyama
2012	A*	`conf`	Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching. ICML Marthinus Christoffel du Plessis, Masashi Sugiyama