maximum likelihood estimation

Learning Determinantal Point Processes by Corrective Negative Sampling AISTATS 2019 Learning Hawkes Processes Under Synchronization Noise ICML 2019 Learning Nonsymmetric Determinantal Point Processes NeurIPS 2019 Lifted Weight Learning of Markov Logic Networks Revisited AISTATS 2019 Mallows ranking models: maximum likelihood estimate and regeneration ICML 2019 Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption UAI 2019 Maximum Likelihood Estimation for Learning Populations of Parameters ICML 2019 Maximum Likelihood for Gaussian Process Classification and Generalized Linear Mixed Models under Case-Control Sampling JMLR 2019 Minimum Divergence vs. Maximum Margin: an Empirical Comparison on Seq2Seq Models ICLR 2019 Model-Free IRL Using Maximum Likelihood Estimation AAAI 2019 Neural Machine Translation with Adequacy-Oriented Learning AAAI 2019 On Fenchel Mini-Max Learning NeurIPS 2019 Optimal Projection Guided Transfer Hashing for Image Retrieval AAAI 2019 Sentence-Wise Smooth Regularization for Sequence to Sequence Learning AAAI 2019 The Impact of Regularization on High-dimensional Logistic Regression NeurIPS 2019 The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling COLT 2019 Word Embedding as Maximum A Posteriori Estimation AAAI 2019 Bootstrapping EM via Power EM and Convergence in the Naive Bayes Model AISTATS 2018 Estimation with Incomplete Data: The Linear Case IJCAI 2018 Generalized Rank-Breaking: Computational and Statistical Tradeoffs JMLR 2018 Generative Bridging Network for Neural Sequence Prediction NAACL 2018 Improving Maximum Likelihood Estimation of Temporal Point Process via Discriminative and Adversarial Learning IJCAI 2018 INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process IJCAI 2018 Learning Registered Point Processes from Idiosyncratic Observations ICML 2018 Learning with Noise-Contrastive Estimation: Easing training by learning to scale COLING 2018