Statistical Learning

Learning Features from Co-occurrences: A Theoretical Analysis COLING 2018 Learning from Comparisons and Choices JMLR 2018 Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds NeurIPS 2018 Learning Single-Index Models in Gaussian Space COLT 2018 Learning under p-Tampering Attacks ALT 2018 Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity NeurIPS 2018 Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator ICML 2018 LHD: Improving Cache Hit Rate by Maximizing Hit Density NSDI 2018 Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design ICML 2018 Linear Spectral Estimators and an Application to Phase Retrieval ICML 2018 Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance COLT 2018 Local Private Hypothesis Testing: Chi-Square Tests ICML 2018 Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning JMLR 2018 Making Classifier Chains Resilient to Class Imbalance ACML 2018 Mallows Models for Top-k Lists NeurIPS 2018 Manifold Structured Prediction NeurIPS 2018 Marginal Singularity, and the Benefits of Labels in Covariate-Shift COLT 2018 Maximum Likelihood Estimation for Mixtures of Spherical Gaussians is NP-hard JMLR 2018 Measuring sentence parallelism using Mahalanobis distances: The NRC unsupervised submissions to the WMT18 Parallel Corpus Filtering shared task EMNLP 2018 MeSH-based dataset for measuring the relevance of text retrieval ACL 2018 Minimax Optimal Bayes Mixtures for Memoryless Sources over Large Alphabets ALT 2018 Minimax Statistical Learning with Wasserstein distances NeurIPS 2018 Model-Agnostic Private Learning NeurIPS 2018 More Robust Doubly Robust Off-policy Evaluation ICML 2018 Multi-Class Learning: From Theory to Algorithm NeurIPS 2018