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Ukraine-Russia war latest: Zelensky to meet Starmer in Downing Street after Kyiv launches drone strike on St Petersburg
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ArrowFlow: Hierarchical Machine Learning in the Space of Permutations
Announce Type: replace Abstract: We introduce ArrowFlow, a machine learning architecture that operates entirely in the space of permutations. Its computational units are ranking filters, learned orderings that compare inputs via Spearman's footrule distance and update through permutation-matrix accumulation, a non-gradient rule rooted in displacement evidence. Layers compose hierarchically: each layer's output ranking becomes the next layer's input, enabling deep ordinal representation...
RobustModelMaker: Coupling Bootstrap Stability Selection with Leakage-Safe Nested Cross-Validation for Scientific Machine Learning
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The Main Barrier to AI Adoption in the Public Sector is Lack of Training: How a Structured Method Increased Productivity in Two Brazilian Government Cases Without Incidents
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Tractable Shapley Values and Interactions via Tensor Networks
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A Novel Data Augmentation Strategy for Robust Deep Learning Classification of Biomedical Time-Series Data: Application to ECG and EEG Analysis
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Backward Coherence and Hidden-State Stability in Recurrent Neural Networks: A Quasi-Reverse-Martingale Theory
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A 65-nm Privacy-Preserving Neuromorphic Encoder With 7.13-nJ Efficiency, 2.38-Mb/mm^2 Item-Memory Density, and Federated Learning Support
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