Statistical Learning

Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers NeurIPS 2016 Train faster, generalize better: Stability of stochastic gradient descent ICML 2016 Truthful Univariate Estimators ICML 2016 Twin Model G-PLDA for Duration Mismatch Compensation in Text-Independent Speaker Verification Interspeech 2016 Unsupervised Risk Estimation Using Only Conditional Independence Structure NeurIPS 2016 Voice Conversion Based on Matrix Variate Gaussian Mixture Model Using Multiple Frame Features Interspeech 2016 A Bayes consistent 1-NN classifier AISTATS 2015 A Bayesian nonparametric procedure for comparing algorithms ICML 2015 Achievability of Asymptotic Minimax Regret by Horizon-Dependent and Horizon-Independent Strategies JMLR 2015 Adaptive Online Learning NeurIPS 2015 A Direct Estimation of High Dimensional Stationary Vector Autoregressions JMLR 2015 A Finite Sample Analysis of the Naive Bayes Classifier JMLR 2015 A General Framework for Fast Stagewise Algorithms JMLR 2015 Agnostic Insurability of Model Classes JMLR 2015 Algorithmic Stability and Uniform Generalization NeurIPS 2015 Alternating Minimization for Regression Problems with Vector-valued Outputs NeurIPS 2015 A Spectral Algorithm for Inference in Hidden semi-Markov Models AISTATS 2015 A Statistical Perspective on Algorithmic Leveraging JMLR 2015 A Unified Framework for Outlier-Robust PCA-like Algorithms ICML 2015 A View of Margin Losses as Regularizers of Probability Estimates JMLR 2015 BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions NeurIPS 2015 Batch Learning from Logged Bandit Feedback through Counterfactual Risk Minimization JMLR 2015 b-bit Marginal Regression NeurIPS 2015 Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs NeurIPS 2015 Closed-form Estimators for High-dimensional Generalized Linear Models NeurIPS 2015