AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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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.
Source localization aims to locate the origin of failures and rumors in complex graphs, which has broad implications for financial systems. However, previous methods commonly assume that the propagation graph is known in advance. In practice, the graph on which failures or information propagate depends on relationships...
The framework of generative flow networks (GFlowNets) is adopted to tackle two core problems in phylogenetics: parsimony-based and Bayesian phylogenetic inference and it is demonstrated that the amortized posterior sampler, PhyloGFN, produces diverse and high-quality evolutionary hypotheses on real benchmark datasets.
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...
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