We have 3 of 22 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
This study proposes an analytical class rebalancing method to compute the optimal rebalancing ratios for imbalanced datasets, and is the first to provide an analytical and parameter-free solution to the problem.
Orthogonal Decomposition for Social Recommendation (ODSR) is proposed, an embedding-space framework that orthogonally decomposes the aggregated social message into an aligned component and an orthogonal deviation, and learns a dimension-wise vector gate to regulate the deviation under ranking supervision.
Class imbalance is a significant challenge in many practical classification tasks, particularly in federated learning (FL), where both global data imbalance and local data heterogeneity across clients worsen the problem. Addressing the class imbalance problem effectively while adhering to privacy constraints remains a...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
