On the Approximation of Kernel functions

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Efficient and Robust Semi-supervised Estimation of Average Treatment Effect with Partially Annotated Treatment and Response

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Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning

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Optimizing Data Collection for Machine Learning

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Unbalanced Kantorovich-Rubinstein distance, plan, and barycenter on nite spaces: A statistical perspective

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Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding

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Rank-one Convexification for Sparse Regression

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gsplat: An Open-Source Library for Gaussian Splatting

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Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming

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Sliced-Wasserstein Distances and Flows on Cartan-Hadamard Manifolds

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Accelerating optimization over the space of probability measures

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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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A model for music emotion recognition and aesthetic education effect evaluation based on deep learning and multimodal data

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

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Orthogonal Bases for Equivariant Graph Learning with Provable k-WL Expressive Power

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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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Hybrid deep learning metaheuristic ensemble framework for enhanced COVID-19 classification using ResNet and particle swarm optimization

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Integrating gene expression and proteomics for breast cancer biomarker prediction through a deep learning framework with SHAP-based explainability

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Application of multimodal machine learning in building ecological assessment

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