Learning Theory

Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes COLT 2017 Query Complexity of Clustering with Side Information NeurIPS 2017 Random Permutation Online Isotonic Regression NeurIPS 2017 Rational Distortions of Learners’ Linguistic Input CoNLL 2017 Recovery Guarantees for One-hidden-layer Neural Networks ICML 2017 Regret Bounds for Lifelong Learning AISTATS 2017 Regret Bounds for Transfer Learning in Bayesian Optimisation AISTATS 2017 Regret Minimization in Behaviorally-Constrained Zero-Sum Games ICML 2017 Regularization and the small-ball method II: complexity dependent error rates JMLR 2017 Relative Fisher Information and Natural Gradient for Learning Large Modular Models ICML 2017 Reliably Learning the ReLU in Polynomial Time COLT 2017 Revenue Optimization with Approximate Bid Predictions NeurIPS 2017 Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces NeurIPS 2017 Risk Bounds for Transferring Representations With and Without Fine-Tuning ICML 2017 Sample and Computationally Efficient Learning Algorithms under S-Concave Distributions NeurIPS 2017 Sample Efficient Policy Search for Optimal Stopping Domains IJCAI 2017 SGD Learns the Conjugate Kernel Class of the Network NeurIPS 2017 Sharp Minima Can Generalize For Deep Nets ICML 2017 Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data AISTATS 2017 Spectral Learning from a Single Trajectory under Finite-State Policies ICML 2017 Spectrally-normalized margin bounds for neural networks NeurIPS 2017 Spectral Methods for Correlated Topic Models AISTATS 2017 Square Hellinger Subadditivity for Bayesian Networks and its Applications to Identity Testing COLT 2017 Statistical and Computational Guarantees for the Baum-Welch Algorithm JMLR 2017 Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference NeurIPS 2017