Event

Masashi Sugiyama, RIKEN and University of Tokyo

Thursday, April 26, 2018 10:30to11:30
Room AA-3195, Pav. André-Aisenstadt, CA

Machine learning from weak supervision - Towards accurate classification with low labeling costs.

Recent advances in machine learning with big labeled data allow us to achieve human-level performance in various tasks such as speech recognition, image understanding, and natural language translation. On the other hand, there are still many application domains where human labor is involved in the data acquisition process and thus the use of massive labeled data is prohibited.  In this talk, I will introduce our recent advances in classification techniques from weak supervision, including classification from positive and unlabeled data, a novel approach to semi-supervised classification, classification from positive-confidence data, and classification from complementary labels
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