Abstract: Multi-label learning deals with training examples each represented by a single instance while associated with multiple class labels. Due to the exponential number of possible label sets to ...

The holiday season is about spending time with loved ones, which also means hearing all of the random words and phrases the young ones have picked up since you saw them last year. No thanks to the ...

Abstract: Computer vision datasets usually present long-tailed training distributions where the classes are not represented with the same number of training samples. This so-called class imbalance ...

In 2023, Ethan Mollick and Lilach Mollick published a paper titled Assigning AI: Seven Approaches for Students, with Prompts. At the time, generative AI tools were far less capable than what we now ...