kernel density estimation

Kernel Smoothing, Mean Shift, and Their Learning Theory with Directional Data JMLR 2021 Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models AISTATS 2021 Adversarial Attacks on Deep Graph Matching NeurIPS 2020 A Fair Classifier Using Kernel Density Estimation NeurIPS 2020 Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations NeurIPS 2020 Estimation of Skill Distribution from a Tournament NeurIPS 2020 Investigating the Visual Lombard Effect with Gabor Based Features Interspeech 2020 Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems AAAI 2020 Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning ICML 2020 Approximate Relative Value Learning for Average-reward Continuous State MDPs UAI 2019 Connectivity-Optimized Representation Learning via Persistent Homology ICML 2019 DBSCAN: Optimal Rates For Density-Based Cluster Estimation JMLR 2019 Discrepancy, Coresets, and Sketches in Machine Learning COLT 2019 Face Alignment With Kernel Density Deep Neural Network ICCV 2019 Neural Empirical Bayes JMLR 2019 Nonparametric Estimation of Probability Density Functions of Random Persistence Diagrams JMLR 2019 Space and Time Efficient Kernel Density Estimation in High Dimensions NeurIPS 2019 Frustratingly Easy Model Ensemble for Abstractive Summarization EMNLP 2018 Kernel Density Estimation for Dynamical Systems JMLR 2018 Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training AISTATS 2018 LoCaTe: Influence Quantification for Location Promotion in Location-based Social Networks IJCAI 2017 On the Consistency of Quick Shift NeurIPS 2017 Product Manifold Filter: Non-Rigid Shape Correspondence via Kernel Density Estimation in the Product Space CVPR 2017 Uniform Convergence Rates for Kernel Density Estimation ICML 2017 Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation NeurIPS 2016