Machine Learning (stat.ML)

On How Well Generative Adversarial Networks Learn Densities: Nonparametric and Parametric Results

Just Interpolate: Kernel ''Ridgeless'' Regression Can Generalize

Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability

Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networks

Statistical Inference for the Population Landscape via Moment Adjusted Stochastic Gradients

Fisher-Rao Metric, Geometry, and Complexity of Neural Networks

Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information

Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP

Computational and Statistical Boundaries for Submatrix Localization in a Large Noisy Matrix

On Detection and Structural Reconstruction of Small-World Random Networks