maximum mean discrepancy

Generative Ratio Matching Networks ICLR 2020 Learning Deep Kernels for Non-Parametric Two-Sample Tests ICML 2020 Learning Kernel Tests Without Data Splitting NeurIPS 2020 Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment NeurIPS 2020 Metric Learning Loss Functions to Reduce Domain Mismatch in the x-Vector Space for Language Recognition Interspeech 2020 More Powerful Selective Kernel Tests for Feature Selection AISTATS 2020 Rescuing neural spike train models from bad MLE NeurIPS 2020 Statistical Optimal Transport posed as Learning Kernel Embedding NeurIPS 2020 SupMMD: A Sentence Importance Model for Extractive Summarization using Maximum Mean Discrepancy EMNLP 2020 Unbalanced Sobolev Descent NeurIPS 2020 Variational Adversarial Kernel Learned Imitation Learning AAAI 2020 A maximum-mean-discrepancy goodness-of-fit test for censored data AISTATS 2019 AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs ICML 2019 Bayesian Posterior Approximation via Greedy Particle Optimization AAAI 2019 Comparative Document Summarisation via Classification AAAI 2019 Cross-Corpus Speech Emotion Recognition Using Semi-Supervised Transfer Non-Negative Matrix Factorization with Adaptation Regularization Interspeech 2019 Differentially Private Distributed Data Summarization under Covariate Shift NeurIPS 2019 Distributionally Robust Optimization and Generalization in Kernel Methods NeurIPS 2019 Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies IJCAI 2019 Implicit Kernel Learning AISTATS 2019 Improving MMD-GAN Training with Repulsive Loss Function ICLR 2019 Improving representation learning in autoencoders via multidimensional interpolation and dual regularizations IJCAI 2019 Interpolating between Optimal Transport and MMD using Sinkhorn Divergences AISTATS 2019 Maximum Mean Discrepancy Gradient Flow NeurIPS 2019 MONK Outlier-Robust Mean Embedding Estimation by Median-of-Means ICML 2019