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瓦瑟斯坦空间的异质性
On Heterogeneity in Wasserstein Space
👁 456 📚 39
有限样本校准保证的事先和可能无概率概率推论
Prior- and likelihood-free probabilistic inference with finite-sample calibration guarantees
👁 464 📚 2
Scalable Text-Embedding-informed Cognitive Diagnosis of Large Language 模型 (Model)s
Scalable Text-Embedding-informed Cognitive Diagnosis of Large Language Models
👁 408 📚 26
Gradient Boosting for Spatial Panel 模型 (Model)s with Random and Fixed Effects
Gradient Boosting for Spatial Panel Models with Random and Fixed Effects
👁 77 📚 1
以有限样本核准风险分析程序的能力
Risk-Calibrated Process Capability Approval with Finite Samples
👁 65 📚 5
高维平均值偏移测试
Deviation Tests for a High-dimensional Mean
👁 356 📚 2
Label Noise Cleaning for Supervised 分类 (Classification) via Bernoulli Random Sampling
Label Noise Cleaning for Supervised Classification via Bernoulli Random Sampling
👁 355 📚 29
A 贝叶斯 (Bayesian) Critique of Rank-Based Methods for Surrogate Marker Evaluation
A Bayesian Critique of Rank-Based Methods for Surrogate Marker Evaluation
👁 65 📚 10
Conformalized Robust Principal Component 分析 (Analysis)
Conformalized Robust Principal Component Analysis
👁 107 📚 36
基于分级的高维回归系数最大sum测试
Rank-based Maxsum test for high dimensional regression coefficient
👁 250 📚 4
Beyond Members:在持久性遗传学无知情况下的地形因果关系
Beyond Means: Topological Causal Effects under Persistent-Homology Ignorability
👁 223 📚 13
基于半连续结果的半参数复方回归,并应用于保健数据
Semiparametric copula-based quantile regression for semicontinuous outcomes with application to heal...
👁 576 📚 49
Integrating Explainable Machine 学习 (Learning) and Mixed-Integer 优化 (Optimization) for Personalized S...
Integrating Explainable Machine Learning and Mixed-Integer Optimization for Personalized Sleep Quali...
👁 272 📚 8
软平均值预期校正出错( SMECE): 概率标签的校正计量
Soft Mean Expected Calibration Error (SMECE): A Calibration Metric for Probabilistic Labels
👁 381 📚 44
一般样本共变矩阵的功能性CLT
Functional CLT for general sample covariance matrices
👁 341 📚 11
基于 Stiefel 倍数上的统一分布的多变量常态测试
Multivariate normality test based on the uniform distribution on the Stiefel manifold
👁 103 📚 46
对函数函数回归的推论:中央限制定理和剩余靴子
Inference for function-on-function regression: central limit theorem and residual bootstrap
👁 48 📚 29
函数主组件回归的高斯和靴子近似值
Gaussian and bootstrap approximations for functional principal component regression
👁 184 📚 36
培训后遗忘的量化特征
A Quantitative Characterization of Forgetting in Post-Training
👁 140 📚 28
化学反应网络比螺旋神经网络学习得更好
Chemical Reaction Networks Learn Better than Spiking Neural Networks
👁 419 📚 10
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