Atmospheric extreme events cause severe damage to human societies and ecosystems.
The frequency and intensity of extremes and other associated events are continuously …

Imbalanced learning constitutes one of the most formidable challenges within data mining
and machine learning. Despite continuous research advancement over the past decades …

Data imbalance exists ubiquitously in real-world visual regressions, eg, age estimation and
pose estimation, hurting the model's generalizability and fairness. Thus, imbalanced …

Real-world data often exhibit imbalanced distributions, where certain target values have
significantly fewer observations. Existing techniques for dealing with imbalanced data focus …

Class imbalance poses new challenges when it comes to classifying data streams. Many
algorithms recently proposed in the literature tackle this problem using a variety of data …

In many real world settings, imbalanced data impedes model performance of learning
algorithms, like neural networks, mostly for rare cases. This is especially problematic for …

The spatial information of rockhead is crucial for the design and construction of tunneling or
underground excavation. Although the conventional site investigation methods (ie borehole …

Single channel target speaker separation (TSS) aims at extracting a speaker's voice from a
mixture of multiple talkers given an enrollment utterance of that speaker. A typical deep …

We present a unified model-based and data-driven approach for quadrupedal planning and
control to achieve dynamic locomotion over uneven terrain. We utilize on-board …

Practical applications of mechanical metamaterials often involve solving inverse problems
aimed at finding microarchitectures that give rise to certain properties. The limited resolution …