Probabilistic Modeling

Identification In Missing Data Models Represented By Directed Acyclic Graphs UAI 2019 Improving the Similarity Measure of Determinantal Point Processes for Extractive Multi-Document Summarization ACL 2019 Interleave Variational Optimization with Monte Carlo Sampling: A Tale of Two Approximate Inference Paradigms AAAI 2019 Interpretable Almost Matching Exactly With Instrumental Variables UAI 2019 Kernel quadrature with DPPs NeurIPS 2019 LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving CVPR 2019 Latent Dirichlet Allocation Based Acoustic Data Selection for Automatic Speech Recognition Interspeech 2019 Latent Dirichlet Allocation for Internet Price War AAAI 2019 Latent Structure Models for Natural Language Processing ACL 2019 Learning Bayesian Networks with Low Rank Conditional Probability Tables NeurIPS 2019 Learning from demonstration with model-based Gaussian process CoRL 2019 Learning Hawkes Processes from a handful of events NeurIPS 2019 Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields IJCAI 2019 Learning Latent Trees with Stochastic Perturbations and Differentiable Dynamic Programming ACL 2019 Learning Mixtures of Plackett-Luce Models from Structured Partial Orders NeurIPS 2019 Learning Nonsymmetric Determinantal Point Processes NeurIPS 2019 Learning Unfaithful K-separable Gaussian Graphical Models JMLR 2019 Learning Vine Copula Models for Synthetic Data Generation AAAI 2019 Leveraging Structural and Semantic Correspondence for Attribute-Oriented Aspect Sentiment Discovery EMNLP 2019 Lifted Hinge-Loss Markov Random Fields AAAI 2019 Marginal Inference in Continuous Markov Random Fields Using Mixtures AAAI 2019 Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption UAI 2019 Markov Random Fields for Collaborative Filtering NeurIPS 2019 Maximum Entropy Distributions: Bit Complexity and Stability COLT 2019 Minimum Stein Discrepancy Estimators NeurIPS 2019