Theory

Information-theoretic lower bounds for convex optimization with erroneous oracles NeurIPS 2015 LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements NeurIPS 2015 Learnability of Influence in Networks NeurIPS 2015 Low-Rank Spectral Learning with Weighted Loss Functions AISTATS 2015 Message Passing for Collective Graphical Models ICML 2015 Minimax Analysis of Active Learning JMLR 2015 Minimax Fixed-Design Linear Regression COLT 2015 Minimum Weight Perfect Matching via Blossom Belief Propagation NeurIPS 2015 Model Selection for Topic Models via Spectral Decomposition AISTATS 2015 Non-Asymptotic Analysis of a New Bandit Algorithm for Semi-Bounded Rewards JMLR 2015 On Elicitation Complexity NeurIPS 2015 On the Accuracy of Self-Normalized Log-Linear Models NeurIPS 2015 On the Asymptotic Normality of an Estimate of a Regression Functional JMLR 2015 On the Equivalence of Moving Entrance Pupil and Radial Distortion for Camera Calibration ICCV 2015 On the Global Linear Convergence of Frank-Wolfe Optimization Variants NeurIPS 2015 On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors NeurIPS 2015 On Theoretical Properties of Sum-Product Networks AISTATS 2015 On the Pseudo-Dimension of Nearly Optimal Auctions NeurIPS 2015 Open Problem: Learning Quantum Circuits with Queries COLT 2015 Open Problem: Recursive Teaching Dimension Versus VC Dimension COLT 2015 Open Problem: The landscape of the loss surfaces of multilayer networks COLT 2015 Open Problem: The Oracle Complexity of Smooth Convex Optimization in Nonstandard Settings COLT 2015 Optimally Combining Classifiers Using Unlabeled Data COLT 2015 Optimal Rates for Random Fourier Features NeurIPS 2015 Precision-Recall-Gain Curves: PR Analysis Done Right NeurIPS 2015