论文列表及评分结果
V-statistics and Variance Estimation.
电商所评分：1
A Theory of the Risk for Optimization with Relaxation and its Application to Support Vector Machines.
电商所评分：5
VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning.
电商所评分：10
On Universal Approximation and Error Bounds for Fourier Neural Operators.
电商所评分：4
Consistency of Gaussian Process Regression in Metric Spaces.
电商所评分：1
Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models.
电商所评分：1
Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions.
电商所评分：2
Recovering shared structure from multiple networks with unknown edge distributions.
电商所评分：5
Exploiting locality in high-dimensional Factorial hidden Markov models.
电商所评分：8
Empirical Risk Minimization under Random Censorship.
电商所评分：4
XAI Beyond Classification: Interpretable Neural Clustering.
电商所评分：8
Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T Processes.
电商所评分：7
Deep Learning in Target Space.
电商所评分：9
Scaling Laws from the Data Manifold Dimension.
电商所评分：4
Interpolating Predictors in High-Dimensional Factor Regression.
电商所评分：3
Near Optimality of Finite Memory Feedback Policies in Partially Observed Markov Decision Processes.
电商所评分：1
Approximate Information State for Approximate Planning and Reinforcement Learning in Partially Observed Systems.
电商所评分：7
Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality.
电商所评分：1
On Generalizations of Some Distance Based Classifiers for HDLSS Data.
电商所评分：2
A Stochastic Bundle Method for Interpolation.
电商所评分：6
TFPnP: Tuning-free Plug-and-Play Proximal Algorithms with Applications to Inverse Imaging Problems.
电商所评分：6
Spatial Multivariate Trees for Big Data Bayesian Regression.
电商所评分：10
Decimated Framelet System on Graphs and Fast G-Framelet Transforms.
电商所评分：2
Universal Approximation in Dropout Neural Networks.
电商所评分：9
Supervised Dimensionality Reduction and Visualization using Centroid-Encoder.
电商所评分：8
Evolutionary Variational Optimization of Generative Models.
电商所评分：5
LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data.
电商所评分：8
Fast and Robust Rank Aggregation against Model Misspecification.
电商所评分：3
On Biased Stochastic Gradient Estimation.
电商所评分：4
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting.
电商所评分：9