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Found 5 papers, 2 papers with code
FlexSSL : A Generic and Efficient Framework for Semi-Supervised Learning
Jointly solving these two tasks allows full utilization of information from both labeled and unlabeled data, thus alleviating the problem of over-reliance on labeled data.
InstructBio: A Large-scale Semi-supervised Learning Paradigm for Biochemical Problems
In the field of artificial intelligence for science, it is consistently an essential challenge to face a limited amount of labeled data for real-world problems.
Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations
We study the problem of offline Imitation Learning (IL) where an agent aims to learn an optimal expert behavior policy without additional online environment interactions.
Enhancing semi-supervised learning via self-interested coalitional learning
Jointly solving these two tasks allows full utilization of information from both labeled and unlabeled data, thus alleviating the problem of over-reliance on labeled data.
CSCAD: Correlation Structure-based Collective Anomaly Detection in Complex System
We propose a correlation structure-based collective anomaly detection (CSCAD) model for high-dimensional anomaly detection problem in large systems, which is also generalizable to semi-supervised or supervised settings.
