Learning Theory

A Sample Complexity Measure with Applications to Learning Optimal Auctions NeurIPS 2017 A Second-order Look at Stability and Generalization COLT 2017 A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening NeurIPS 2017 A survey of Algorithms and Analysis for Adaptive Online Learning JMLR 2017 Asymptotic Analysis of Objectives Based on Fisher Information in Active Learning JMLR 2017 Asymptotic behavior of Support Vector Machine for spiked population model JMLR 2017 A Unified Framework for Structured Prediction: From Theory to Practice EMNLP 2017 Bernoulli Rank-1 Bandits for Click Feedback IJCAI 2017 Binary and Multi-Bit Coding for Stable Random Projections AISTATS 2017 Boltzmann Exploration Done Right NeurIPS 2017 Boundary Crossing for General Exponential Families ALT 2017 Breaking the Curse of Dimensionality with Convex Neural Networks JMLR 2017 Bridging Supervised Learning and Test-Based Co-optimization JMLR 2017 Clustering Stable Instances of Euclidean k-means. NeurIPS 2017 Collaborative Clustering: Sample Complexity and Efficient Algorithms ALT 2017 Collaborative PAC Learning NeurIPS 2017 Contextual Decision Processes with low Bellman rank are PAC-Learnable ICML 2017 Convergence Analysis of Two-layer Neural Networks with ReLU Activation NeurIPS 2017 Convergence of Gradient EM on Multi-component Mixture of Gaussians NeurIPS 2017 Corralling a Band of Bandit Algorithms COLT 2017 Counterfactual Learning from Bandit Feedback under Deterministic Logging : A Case Study in Statistical Machine Translation EMNLP 2017 Data-Efficient Policy Evaluation Through Behavior Policy Search ICML 2017 Dealing with Range Anxiety in Mean Estimation via Statistical Queries ALT 2017 Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks ICML 2017 Diameter-Based Active Learning ICML 2017