Probabilistic Modeling

Faithfulness of Probability Distributions and Graphs JMLR 2017 Faster Greedy MAP Inference for Determinantal Point Processes ICML 2017 Fast Sparse Gaussian Markov Random Fields Learning Based on Cholesky Factorization IJCAI 2017 From Segmentation to Analyses: a Probabilistic Model for Unsupervised Morphology Induction EACL 2017 Gain Compensation for Fast i-Vector Extraction Over Short Duration Interspeech 2017 Gaussian process based nonlinear latent structure discovery in multivariate spike train data NeurIPS 2017 Hierarchical Implicit Models and Likelihood-Free Variational Inference NeurIPS 2017 Hierarchical Methods of Moments NeurIPS 2017 High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm ICML 2017 Hyperspherical Query Likelihood Models with Word Embeddings IJCNLP 2017 Improving Semantic Composition with Offset Inference ACL 2017 Inferring Generative Model Structure with Static Analysis NeurIPS 2017 Integrating Specialized Classifiers Based on Continuous Time Markov Chain IJCAI 2017 Inverse Filtering for Hidden Markov Models NeurIPS 2017 Latent Variable Dialogue Models and their Diversity EACL 2017 Lean Crowdsourcing: Combining Humans and Machines in an Online System CVPR 2017 Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo ICML 2017 Learning Determinantal Point Processes with Moments and Cycles ICML 2017 Learning Hawkes Processes from Short Doubly-Censored Event Sequences ICML 2017 Learning Local Dependence In Ordered Data JMLR 2017 Learning Overcomplete HMMs NeurIPS 2017 Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding NeurIPS 2017 Learning the Structure of Variable-Order CRFs: a finite-state perspective EMNLP 2017 Learning Topic-Sensitive Word Representations ACL 2017 Leveraging Node Attributes for Incomplete Relational Data ICML 2017