Abstract Out-of-distribution (OOD) detection is critical to ensuring the reliability and safety of
machine learning systems. For instance, in autonomous driving, we would like the driving …

Out-of-Distribution (OOD) detection separates ID (In-Distribution) data and OOD data from
input data through a model. This problem has attracted increasing attention in the area of …

As one of state-of-the-art supervised novelty detection models, support vector machine-
supervised novelty detection (SVM-SND) can recognize whether a test instance is a novelty …

Fake news or misinformation is the information or stories intentionally created to deceive or
mislead the readers. Nowadays, social media platforms have become the ripe grounds for …

The problem of class imbalance has always been considered as a significant challenge to
traditional machine learning and the emerging deep learning research communities. A …

One of the most time-critical challenges for the Natural Language Processing (NLP)
community is to combat the spread of fake news and misinformation. Existing approaches for …

Navigation in natural outdoor environments requires a robust and reliable traversability
classification method to handle the plethora of situations a robot can encounter. Binary …

Recommendation systems have shown great potential to solve the information explosion
problem and enhance user experience in various online applications, which recently …

Science teams for rover-based planetary exploration missions like the Mars Science
Laboratory Curiosity rover have limited time for analyzing new data before making decisions …

Ongoing planetary exploration missions are returning large volumes of image data.
Identifying surface changes in these images, eg, new impact craters, is critical for …