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Found 6 papers, 2 papers with code
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.
Cost-Sensitive Active Learning for Incomplete Data
A reasonable machine learning scenario involves obtaining certain values and labels at cost on request.
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.
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications
This paper provides a comprehensive review of epistemic uncertainty learning techniques in supervised learning over the last five years.
Adversarial Learning with Cost-Sensitive Classes
This paper proposes a framework combining cost-sensitive classification and adversarial learning together to train a model that can distinguish between protected and unprotected classes, such that the protected classes are less vulnerable to adversarial examples.
Incorporating Hidden Layer representation into Adversarial Attacks and Defences
In this paper, we propose a defence strategy to improve adversarial robustness by incorporating hidden layer representation.
