Statistical Learning

The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models NeurIPS 2018 The Trajectory of Voice Onset Time with Vocal Aging Interspeech 2018 The Well-Tempered Lasso ICML 2018 Tight Bounds for Collaborative PAC Learning via Multiplicative Weights NeurIPS 2018 Toeplitz Inverse Covariance-based Clustering of Multivariate Time Series Data IJCAI 2018 Topological mixture estimation ICML 2018 To Tune or Not to Tune the Number of Trees in Random Forest JMLR 2018 Unbiased Objective Estimation in Predictive Optimization ICML 2018 Uncertainty-aware generative models for inferring document class prevalence EMNLP 2018 Uncovering Causality from Multivariate Hawkes Integrated Cumulants JMLR 2018 Unsupervised Morphology Learning with Statistical Paradigms COLING 2018 Uplift Modeling from Separate Labels NeurIPS 2018 Using J-K-fold Cross Validation To Reduce Variance When Tuning NLP Models COLING 2018 Using Linguistic Resources to Evaluate the Quality of Annotated Corpora COLING 2018 Variance Regularized Counterfactual Risk Minimization via Variational Divergence Minimization ICML 2018 Variational Network Inference: Strong and Stable with Concrete Support ICML 2018 Why Adaptively Collected Data Have Negative Bias and How to Correct for It AISTATS 2018 Yes, but Did It Work?: Evaluating Variational Inference ICML 2018 Z-Transforms and its Inference on Partially Observable Point Processes IJCAI 2018 A Bayesian Mixed-Effects Model to Learn Trajectories of Changes from Repeated Manifold-Valued Observations JMLR 2017 Achieving Optimal Misclassification Proportion in Stochastic Block Models JMLR 2017 A Learning Theory of Ranking Aggregation AISTATS 2017 Algorithmic Stability and Hypothesis Complexity ICML 2017 A Linear-Time Kernel Goodness-of-Fit Test NeurIPS 2017 A Minimax Optimal Algorithm for Crowdsourcing NeurIPS 2017