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Three trees suffice for a constant stretch in minor-free graphs
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Hierarchical 贝叶斯 (Bayesian) Calibration with 贝叶斯 (Bayesian) Committee Machine
Hierarchical Bayesian Calibration with Bayesian Committee Machine
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Bagging Robustly Learns VC Classes with Linear Sample Complexity
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Hyper-V uniform ergodicity of Markov chains
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Defensive Boosting for Online Probabilistic Forecasting
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Linear-cost Polyharmonic Spline Interpolation of Arbitrary Degree
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Asymmetric Palette Sparsification, Slightly Simplified
👁 135 📚 11
Optimal Stratification of a Sampling Frame: A Comparative Study of Classical, Quantum, and Quantum-I...
👁 133 📚 22
Matchings via Random Greedy Independent Set: A Simpler Algorithm and 分析 (Analysis)
Matchings via Random Greedy Independent Set: A Simpler Algorithm and Analysis
👁 113 📚 7
Sparse Variable Sharpening in High-Dimensional Kernel Density 估计 (Estimation)
Sparse Variable Sharpening in High-Dimensional Kernel Density Estimation
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Where Treewidth and Pathwidth Diverge: Towards a Uniform Kernel for Pathwidth-$η$ Deletion
👁 52 📚 19
Structured Dimension-Matched Joint Variational Transdimensional 推断 (Inference)
Structured Dimension-Matched Joint Variational Transdimensional Inference
👁 36 📚 29
Rigorous Low-Degree Implications for Planted Subgraph Detection: Noise and Treewidth
👁 72 📚 29
A space of inference spaces in the space sciences - Parametric 贝叶斯 (Bayesian) inference in astronomy...
A space of inference spaces in the space sciences - Parametric Bayesian inference in astronomy, cosm...
👁 209 📚 4
Optimal Rates for 学习 (Learning) with Monotone Adversaries
Optimal Rates for Learning with Monotone Adversaries
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学习 (Learning) Latent Memory States from Longitudinal Athlete Monitoring 数据 (Data)
Learning Latent Memory States from Longitudinal Athlete Monitoring Data
👁 120 📚 17
An Optimal Agnostic PAC Algorithm
👁 161 📚 17
Stochastic Emulation using Generalized Stratified Sampling for Performance-Based Risk 优化 (Optimizati...
Stochastic Emulation using Generalized Stratified Sampling for Performance-Based Risk Optimization o...
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If it is Good Then Drop it -- a Spiteful Poisson Process for Submodular Maximization
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Two-Stage Design with Sample Size Re-estimation Using gsDesign
👁 114 📚 23
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海洋智能体
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