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Learning Theory

5,312 papers

Papers per year

Papers

On the Interaction Effects Between Prediction and Clustering AISTATS 2019
Logarithmic Regret for Online Gradient Descent Beyond Strong Convexity AISTATS 2019
Learning Mixtures of Smooth Product Distributions: Identifiability and Algorithm AISTATS 2019
Foundations of Sequence-to-Sequence Modeling for Time Series AISTATS 2019
Lifelong Optimization with Low Regret AISTATS 2019
Support and Invertibility in Domain-Invariant Representations AISTATS 2019
Classification using margin pursuit AISTATS 2019
Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior AISTATS 2019
On Kernel Derivative Approximation with Random Fourier Features AISTATS 2019
Deep Neural Networks Learn Non-Smooth Functions Effectively AISTATS 2019
Fisher-Rao Metric, Geometry, and Complexity of Neural Networks AISTATS 2019
Bandit Online Learning with Unknown Delays AISTATS 2019
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach AISTATS 2019
On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition AISTATS 2019
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent AISTATS 2019
Are we there yet? Manifold identification of gradient-related proximal methods AISTATS 2019
Model Consistency for Learning with Mirror-Stratifiable Regularizers AISTATS 2019
From Cost-Sensitive Classification to Tight F-measure Bounds AISTATS 2019
A Continuous-Time View of Early Stopping for Least Squares Regression AISTATS 2019
Top Feasible Arm Identification AISTATS 2019
Does data interpolation contradict statistical optimality? AISTATS 2019
Statistical Learning under Nonstationary Mixing Processes AISTATS 2019
On Structure Priors for Learning Bayesian Networks AISTATS 2019
Exponential Weights on the Hypercube in Polynomial Time AISTATS 2019
Sharp Analysis of Learning with Discrete Losses AISTATS 2019