Data-Derived Weak Universal Consistency

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MurTree: Optimal Decision Trees via Dynamic Programming and Search

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Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting

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On Biased Stochastic Gradient Estimation

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Fast and Robust Rank Aggregation against Model Misspecification

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LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data

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Evolutionary Variational Optimization of Generative Models

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Supervised Dimensionality Reduction and Visualization using Centroid-Encoder

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Universal Approximation in Dropout Neural Networks

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Decimated Framelet System on Graphs and Fast G-Framelet Transforms

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Spatial Multivariate Trees for Big Data Bayesian Regression

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TFPnP: Tuning-free Plug-and-Play Proximal Algorithms with Applications to Inverse Imaging Problems

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A Stochastic Bundle Method for Interpolation

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On Generalizations of Some Distance Based Classifiers for HDLSS Data

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Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality

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Approximate Information State for Approximate Planning and Reinforcement Learning in Partially Observed Systems

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Near Optimality of Finite Memory Feedback Policies in Partially Observed Markov Decision Processes

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Interpolating Predictors in High-Dimensional Factor Regression

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Scaling Laws from the Data Manifold Dimension

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Deep Learning in Target Space

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