kullback-leibler divergence

Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space NeurIPS 2021 Scalable First-Order Methods for Robust MDPs AAAI 2021 Two-stage Training for Learning from Label Proportions IJCAI 2021 Understanding and Improving Lexical Choice in Non-Autoregressive Translation ICLR 2021 Variational Fair Clustering AAAI 2021 Variational refinement for importance sampling using the forward Kullback-Leibler divergence UAI 2021 A Batch Normalized Inference Network Keeps the KL Vanishing Away ACL 2020 An approximate KLD based experimental design for models with intractable likelihoods AISTATS 2020 An NMF-HMM Speech Enhancement Method Based on Kullback-Leibler Divergence Interspeech 2020 Consistent recovery threshold of hidden nearest neighbor graphs COLT 2020 Data-dependent Gaussian Prior Objective for Language Generation ICLR 2020 Distributionally Robust Counterfactual Risk Minimization AAAI 2020 Distributionally Robust Parametric Maximum Likelihood Estimation NeurIPS 2020 Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards NeurIPS 2020 Functional Regularisation for Continual Learning with Gaussian Processes ICLR 2020 Greedy inference with structure-exploiting lazy maps NeurIPS 2020 Markovian Score Climbing: Variational Inference with KL(p||q) NeurIPS 2020 Model Fusion with Kullback-Leibler Divergence ICML 2020 Posterior Re-calibration for Imbalanced Datasets NeurIPS 2020 Probabilistic Regression for Visual Tracking CVPR 2020 Sinkhorn Regression IJCAI 2020 Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical Models AISTATS 2020 Variational Bayesian Unlearning NeurIPS 2020 A Theory of Regularized Markov Decision Processes ICML 2019 Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization NeurIPS 2019