Lingqiao Liu

To Balance or Not to Balance: An Embarrassingly Simple Approach for Learning with Long-Tailed Distributions.

2019 · arXiv (Cornell University)

Real-world visual data often exhibits a long-tailed distribution, where some ''head'' classes have a large number of samples, yet only a few samples are available for ''tail'' classes. Such imbalanced distribution causes a great challenge …

Source-Free Unsupervised Domain Adaptation with Hypothesis Consolidation of Prediction Rationale

2024 · arXiv (Cornell University)

Source-Free Unsupervised Domain Adaptation (SFUDA) is a challenging task where a model needs to be adapted to a new domain without access to target domain labels or source domain data. The primary difficulty in this …