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DEDPUL: Method for Mixture Proportion Estimation and Positive-Unlabeled Classification based on Density Estimation
We develop a novel method (DEDPUL) that simultaneously solves two problems concerning the contaminated Unlabeled (U) sample: estimates the proportions of the mixing components (P and N) in U, and classifies U. Expand
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DEDPUL: Difference-of-Estimated-Densities-based Positive-Unlabeled Learning
Positive-Unlabeled Learning is an analog to supervised binary classification for the case when the negative (N) sample in the training set is noisy. Expand
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Identifying Bid Leakage in Procurement Auctions: Machine Learning Approach
We propose a novel machine-learning-based approach to detect bid leakage in first-price sealed-bid auctions. Expand
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First Results of the FAST-S/X Sessions with New VGOS Antennas
DEDPUL: Method for Positive-Unlabeled Learning based on Density Estimation
Positive-Unlabeled Classification is an analog of binary classification for the case when the Negative (N) sample in the training set is contaminated with latent instances of the Positive (P) classExpand
Numerical Method for Coupled Nonlinear Schrödinger Equations in Few Mode Fiber
This paper discusses approaches to the numerical integration of the coupled nonlinear Schrödinger equations system in case of few-mode wave propagation. The wave propagation assumes the propagationExpand