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ORCIDMarthinus Christoffel du Plessis
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- affiliation: University of Tokyo, Sugiyama Laboratory
- affiliation: Tokyo Institute of Technology, Sugiyama Laboratory
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2010 – 2019
- 2018
[j9]Yung-Kyun Noh, Masashi Sugiyama
, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee:
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. Neural Comput. 30(7) (2018)- 2017
- [j8]Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama:
Class-prior estimation for learning from positive and unlabeled data. Mach. Learn. 106(4): 463-492 (2017) - [c12]Tomoya Sakai, Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama:
Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data. ICML 2017: 2998-3006 - [c11]Ryuichi Kiryo, Gang Niu, Marthinus Christoffel du Plessis, Masashi Sugiyama:
Positive-Unlabeled Learning with Non-Negative Risk Estimator. NIPS 2017: 1675-1685 - [i8]Ryuichi Kiryo, Gang Niu, Marthinus Christoffel du Plessis, Masashi Sugiyama:
Positive-Unlabeled Learning with Non-Negative Risk Estimator. CoRR abs/1703.00593 (2017) - 2016
- [j7]Hideko Kawakubo, Marthinus Christoffel du Plessis, Masashi Sugiyama:
Computationally Efficient Class-Prior Estimation under Class Balance Change Using Energy Distance. IEICE Trans. Inf. Syst. 99-D(1): 176-186 (2016) - [c10]Gang Niu, Marthinus Christoffel du Plessis, Tomoya Sakai, Yao Ma, Masashi Sugiyama:
Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning. NIPS 2016: 1199-1207 - [i7]Gang Niu, Marthinus Christoffel du Plessis, Tomoya Sakai, Masashi Sugiyama:
Theoretical Comparisons of Learning from Positive-Negative, Positive-Unlabeled, and Negative-Unlabeled Data. CoRR abs/1603.03130 (2016) - [i6]Tomoya Sakai, Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama:
Beyond the Low-density Separation Principle: A Novel Approach to Semi-supervised Learning. CoRR abs/1605.06955 (2016) - [i5]Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama:
Class-prior Estimation for Learning from Positive and Unlabeled Data. CoRR abs/1611.01586 (2016) - 2015
- [j6]Marthinus Christoffel du Plessis, Hiroaki Shiino, Masashi Sugiyama:
Online Direct Density-Ratio Estimation Applied to Inlier-Based Outlier Detection. Neural Comput. 27(9): 1899-1914 (2015) - [c9]Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama:
Class-prior Estimation for Learning from Positive and Unlabeled Data. ACML 2015: 221-236 - [c8]Tuan Duong Nguyen, Marthinus Christoffel du Plessis, Masashi Sugiyama:
Continuous Target Shift Adaptation in Supervised Learning. ACML 2015: 285-300 - [c7]Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama:
Convex Formulation for Learning from Positive and Unlabeled Data. ICML 2015: 1386-1394 - 2014
- [j5]Marthinus Christoffel du Plessis, Masashi Sugiyama:
Class Prior Estimation from Positive and Unlabeled Data. IEICE Trans. Inf. Syst. 97-D(5): 1358-1362 (2014) - [j4]Tuan Duong Nguyen, Marthinus Christoffel du Plessis, Takafumi Kanamori, Masashi Sugiyama:
Constrained Least-Squares Density-Difference Estimation. IEICE Trans. Inf. Syst. 97-D(7): 1822-1829 (2014) - [j3]Marthinus Christoffel du Plessis, Masashi Sugiyama:
Semi-supervised learning of class balance under class-prior change by distribution matching. Neural Networks 50: 110-119 (2014) - [c6]Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee:
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. AISTATS 2014: 669-677 - [c5]Gang Niu, Bo Dai, Marthinus Christoffel du Plessis, Masashi Sugiyama:
Transductive Learning with Multi-class Volume Approximation. ICML 2014: 1377-1385 - [c4]Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama:
Analysis of Learning from Positive and Unlabeled Data. NIPS 2014: 703-711 - [i4]Gang Niu, Bo Dai, Marthinus Christoffel du Plessis, Masashi Sugiyama:
Transductive Learning with Multi-class Volume Approximation. CoRR abs/1402.0288 (2014) - 2013
- [j2]Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Masao Yamanaka, Makoto Yamada, Taiji Suzuki, Takafumi Kanamori:
Direct Divergence Approximation between Probability Distributions and Its Applications in Machine Learning. J. Comput. Sci. Eng. 7(2): 99-111 (2013) - [j1]Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi:
Density-Difference Estimation. Neural Comput. 25(10): 2734-2775 (2013) - [c3]Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama:
Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances. TAAI 2013: 1-6 - [i3]Marthinus Christoffel du Plessis, Masashi Sugiyama:
Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances. CoRR abs/1305.0103 (2013) - 2012
- [c2]Marthinus Christoffel du Plessis, Masashi Sugiyama:
Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching. ICML 2012 - [c1]Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi:
Density-Difference Estimation. NIPS 2012: 692-700 - [i2]Marthinus Christoffel du Plessis, Masashi Sugiyama:
Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching. CoRR abs/1206.4677 (2012) - [i1]Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi:
Density-Difference Estimation. CoRR abs/1207.0099 (2012)
Coauthor Index
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