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Found 6 papers, 2 papers with code
An Accelerator for Rule Induction in Fuzzy Rough Theory
First, a rule induction method based on consistence degree, called Consistence-based Value Reduction (CVR), is proposed and used as basis to accelerate.
Semi-Supervised Learning via Weight-aware Distillation under Class Distribution Mismatch
Specifically, WAD captures adaptive weights and high-quality pseudo labels to target instances by exploring point mutual information (PMI) in representation space to maximize the role of unlabeled data and filter unknown categories.
Contrastive Coding for Active Learning Under Class Distribution Mismatch
However, its performance deteriorates under class distribution mismatch, wherein the unlabeled data contain many samples out of the class distribution of labeled data.
Oracle-guided Contrastive Clustering
Accordingly, the query results, guided by oracles with distinctive demands, may drive the OCC's clustering results in a desired orientation.
Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model
In this work, a general framework (APES) is built up to strengthen model privacy under personalized local privacy by leveraging the privacy amplification effect of the shuffle model.
Superclass Learning With Representation Enhancement
In many real scenarios, data are often divided into a handful of artificial super categories in terms of expert knowledge rather than the representations of images.
