Mutual Information Regularized Feature-Level Frankenstein for Discriminative …

Deep learning recognition approaches can potentially perform better if we can extract a discriminative representation that controllably separates nuisance factors. In this paper, we propose a novel…

Instance-Dependent Positive and Unlabeled Learning With Labeling Bias Estimation

This paper studies instance-dependent P ositive and U nlabeled (PU) classification, where whether a positive example will be labeled (indicated by s ) is not only related to the class label y , but…

Centroid Estimation With Guaranteed Efficiency : A General Framework for Weak…

Semi Supervised Learning Artificial Intelligence, Statistical Analysis, Weakly Supervised Learning, CEGE, Incomplete Supervision, Inexact Supervision, Inaccurate Supervision, Unbiased Risk Estimato…

Learning Content-Weighted Deep Image Compression

Learning-based lossy image compression usually involves the joint optimization of rate-distortion performance, and requires to cope with the spatial variation of image content and contextual depend…

Incremental Semi-Supervised Clustering Ensemble for High Dimensional Data Clu…