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This work introduces SPatial coHErent risk control for REplay (SPHERE), a general replay-allocation method applicable across a broad range of learning settings and demonstrates that SPHERE improves accuracy and reduces forgetting across noisy-label vision tasks, continual language-model instruction tuning, and code-gen...
Outliers are essential for evaluating and improving the robustness of machine learning systems, especially when future distributions may differ significantly from historical training data. In high-stakes applications, robustness often depends on rare cases that finite datasets fail to capture, making simple resampling...
HiTOC is proposed, a Hierarchical Topological Ordering framework for Causal discovery that constructs the global causal structure via layer-wise integration of local orderings over induced subsets by Markov Blanket and achieves state-of-the-art performance in both accuracy and scalability, particularly in high-dimensio...
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