curse of dimensionality

Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization NeurIPS 2022 Shallow and Deep Networks are Near-Optimal Approximators of Korobov Functions ICLR 2022 Synergy and Symmetry in Deep Learning: Interactions between the Data, Model, and Inference Algorithm ICML 2022 Two-Sample Test with Kernel Projected Wasserstein Distance AISTATS 2022 A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation COLT 2021 Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions AISTATS 2021 Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space NeurIPS 2021 Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning NeurIPS 2021 Parametric Complexity Bounds for Approximating PDEs with Neural Networks NeurIPS 2021 Solving high-dimensional parabolic PDEs using the tensor train format ICML 2021 Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness ICML 2020 Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning NeurIPS 2020 On Convergence of Nearest Neighbor Classifiers over Feature Transformations NeurIPS 2020 Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality NeurIPS 2020 Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information JMLR 2020 Survey on Feature Transformation Techniques for Data Streams IJCAI 2020 When Do Neural Networks Outperform Kernel Methods? NeurIPS 2020 Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality ICLR 2019 Unsupervised Low-Rank Representations for Speech Emotion Recognition Interspeech 2019 Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information ICML 2018 On the Behavior of Intrinsically High-Dimensional Spaces: Distances, Direct and Reverse Nearest Neighbors, and Hubness JMLR 2018 Product Kernel Interpolation for Scalable Gaussian Processes AISTATS 2018 Breaking the Curse of Dimensionality with Convex Neural Networks JMLR 2017 Fast k-Nearest Neighbour Search via Prioritized DCI ICML 2017 Rates of estimation for determinantal point processes COLT 2017