kl divergence

An explicit analysis of the entropic penalty in linear programming COLT 2018 Calibrating Noise to Variance in Adaptive Data Analysis COLT 2018 Composite Functional Gradient Learning of Generative Adversarial Models ICML 2018 Convergence of Langevin MCMC in KL-divergence ALT 2018 Generative Bridging Network for Neural Sequence Prediction NAACL 2018 Legendre Decomposition for Tensors NeurIPS 2018 On Learning Markov Chains NeurIPS 2018 On Unifying Deep Generative Models ICLR 2018 Parameterized hardness of active inference PGM 2018 Spherical Latent Spaces for Stable Variational Autoencoders EMNLP 2018 AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms NeurIPS 2017 Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction NeurIPS 2017 Dual Discriminator Generative Adversarial Nets NeurIPS 2017 On the Linguistic Relevance of Speech Units Learned by Unsupervised Acoustic Modeling Interspeech 2017 Stein Variational Gradient Descent as Gradient Flow NeurIPS 2017 GMM-Free Flat Start Sequence-Discriminative DNN Training Interspeech 2016 Measuring the reliability of MCMC inference with bidirectional Monte Carlo NeurIPS 2016 Provable Bayesian Inference via Particle Mirror Descent AISTATS 2016 Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NeurIPS 2016 Competitive Distribution Estimation: Why is Good-Turing Good NeurIPS 2015 Data modeling with the elliptical gamma distribution AISTATS 2015 Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation AISTATS 2015 KL Divergence Based Agglomerative Clustering for Automated Vitiligo Grading CVPR 2015 Large-Scale Markov Decision Problems with KL Control Cost and its Application to Crowdsourcing ICML 2015 On Learning Distributions from their Samples COLT 2015