Statistical Learning

Learning Unfaithful K-separable Gaussian Graphical Models JMLR 2019 Least Squares Estimation of Weakly Convex Functions AISTATS 2019 Leveraging Observations in Bandits: Between Risks and Benefits AAAI 2019 Lexical concreteness in narrative ACL 2019 Lifted Weight Learning of Markov Logic Networks Revisited AISTATS 2019 Lifting high-dimensional non-linear models with Gaussian regressors AISTATS 2019 Likelihood-Free Overcomplete ICA and Applications In Causal Discovery NeurIPS 2019 Linear Queries Estimation with Local Differential Privacy AISTATS 2019 Localized Structured Prediction NeurIPS 2019 Locally Private Mean Estimation: Z-test and Tight Confidence Intervals AISTATS 2019 LogAnomaly: Unsupervised Detection of Sequential and Quantitative Anomalies in Unstructured Logs IJCAI 2019 Lower Bound of Locally Differentially Private Sparse Covariance Matrix Estimation IJCAI 2019 Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments NeurIPS 2019 Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption UAI 2019 Maximum Entropy Distributions: Bit Complexity and Stability COLT 2019 Maximum Likelihood Estimation for Learning Populations of Parameters ICML 2019 McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds NeurIPS 2019 Measuring and Modeling Language Change NAACL 2019 Minimal Achievable Sufficient Statistic Learning ICML 2019 Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases NeurIPS 2019 Minimizers of the Empirical Risk and Risk Monotonicity NeurIPS 2019 Minimum Stein Discrepancy Estimators NeurIPS 2019 Mixed Effects Neural Networks (MeNets) With Applications to Gaze Estimation CVPR 2019 Model Consistency for Learning with Mirror-Stratifiable Regularizers AISTATS 2019 Modeling Word Emotion in Historical Language: Quantity Beats Supposed Stability in Seed Word Selection NAACL 2019