Accelerating optimization over the space of probability measures

Subjects: “…Artificial Intelligence & Machine Learning…”
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Bayesian Multi-Group Gaussian Process Models for Heterogeneous Group-Structured Data

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Honey, I Shrunk the Hypothesis Space (Through Logical Preprocessing)

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Orchestrated intelligence: an adaptive multi-agent architecture for high-frequency options risk management

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Research on fashion brand narrative generation and personalized communication strategy based on knowledge graph and LLM

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Research on cross-border enterprise knowledge sharing mechanism based on federated graph neural network and differential privacy collaboration

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Design of an integrated federated large language models for semantic reasoning and self-organizing 6G networks

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Robustness and authorship bias of large language models in scientific abstracts scoring

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Bibliometric analysis of artificial intelligence application in bioinformatics

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Artificial neural network optimized by Honey Badger Algorithm for predicting and explaining properties of 3D printed objects

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Optimal Experiment Design for Causal Effect Identification

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Context-aware transformer models for accounting-based inventory prediction and supply chain cost optimization

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Mean Aggregator is More Robust than Robust Aggregators under Label Poisoning Attacks on Distributed Heterogeneous Data

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Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick

Subjects: “…Artificial Intelligence & Machine Learning…”
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Directed Cyclic Graphs for Simultaneous Discovery of Time-Lagged and Instantaneous Causality from Longitudinal Data Using Instrumental Variables

Subjects: “…Artificial Intelligence & Machine Learning…”
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Bayesian Sparse Gaussian Mixture Model for Clustering in High Dimensions

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Regularizing Hard Examples Improves Adversarial Robustness

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Random ReLU Neural Networks as Non-Gaussian Processes

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Riemannian Bilevel Optimization

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Error estimation and adaptive tuning for unregularized robust M-estimator

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