research
∙
06/19/2022
Label and Distribution-discriminative Dual Representation Learning for Out-of-Distribution Detection
To classify in-distribution samples, deep neural networks learn label-di...
share
research
∙
06/19/2022
Out-of-distribution Detection by Cross-class Vicinity Distribution of In-distribution Data
Deep neural networks only learn to map in-distribution inputs to their c...
research
∙
06/19/2022
Supervision Adaptation Balances In-Distribution Generalization and Out-of-Distribution Detection
When there is a discrepancy between in-distribution (ID) samples and out...
research
∙
06/19/2022
Gray Learning from Non-IID Data with Out-of-distribution Samples
The quality of the training data annotated by experts cannot be guarante...
research
∙
02/12/2022
Coupling Online-Offline Learning for Multi-distributional Data Streams
The distributions of real-life data streams are usually nonstationary, w...
research
∙
08/23/2021