☆ 4.7 Article

Modeling PU learning using probabilistic logic programming

MACHINE LEARNING (2023)

Parameter Learning in ProbLog with Annotated Disjunctions

Wen-Chi Yang et al.

Summary: EMPLiFI is an EM-based parameter learning technique that improves the efficiency of learning by exploiting the rule-based structure of logic programs. It enables parameter learning of multi-head annotated disjunctions in ProbLog programs.

ADVANCES IN INTELLIGENT DATA ANALYSIS XX, IDA 2022 (2022)

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Article Computer Science, Artificial Intelligence

Instance-Dependent Positive and Unlabeled Learning With Labeling Bias Estimation

Chen Gong et al.

Summary: This paper proposes an instance-dependent Positive and Unlabeled (PU) classification algorithm based on graphical models and optimization techniques like EM and Adam, which effectively obtains the labeling probability of positive examples and the classifier based on observations. Theoretical analysis proves the existence of critical solutions and their local uniqueness, along with an upper bound estimation of generalization error for the algorithm. Empirical results demonstrate the significant advantage of the proposed method over existing PU approaches on various datasets.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2022)

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Article Computer Science, Artificial Intelligence