Table of Contents

Preface xiii
I Machine Learning from Weak Supervision
1 Introduction 3
2 Formulation and Notation 21
3 Supervised Classification 35
II Weakly Supervised Learning for Binary Classification
4 Positive-Unlabeled (PU) Classification 67
5 Positive-Negative-Unlabeled (PNU) Classification 85
6 Positive-Confidence (Pconf) Classification 111
7 Pairwise-Constraint Classification 127
8 Unlabeled-Unlabeled (UU) Classification 149
III Weakly Supervised Learning for Multi-class Classification
9 Complementary-Label Classification 177
10 Partial-Label Classification 193
IV Advanced Topics and Perspectives
11 Non-Negative Correction for Weakly Supervised Classification 207
12 Class-Prior Estimation 239
13 Conclusions and Prospects 275
Notes 279
Bibliography 283
Index 293

About the Author

Masashi Sugiyama is Director of the RIKEN Center for Advanced Intelligence Project and Professor of Computer Science at the University of Tokyo. Han Bao is a PhD student in the Department of Computer Science at the University of Tokyo and Research Assistant at the RIKEN Center for Advanced Intelligence Project. Takashi Ishida is a Lecturer at the University of Tokyo and Visiting Scientist at the RIKEN Center for Advanced Intelligence Project. Nan Lu is a PhD student in the Department of Complexity Science and Engineering at the University of Tokyo and Research Assistant at the RIKEN Center for Advanced Intelligence Project. Tomoya Sakai is Senior Researcher at NEC Corporation and Visiting Scientist at the RIKEN Center for Advanced Intelligence Project. Gang Niu is Research Scientist in the Imperfect Information Learning Team at the RIKEN Center for Advanced Intelligence Project.