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Statistical Learning

4,076 papers

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Papers

Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees AISTATS 2019
On Kernel Derivative Approximation with Random Fourier Features AISTATS 2019
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows AISTATS 2019
Deep Neural Networks Learn Non-Smooth Functions Effectively AISTATS 2019
Hadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication AISTATS 2019
A Swiss Army Infinitesimal Jackknife AISTATS 2019
Subsampled Renyi Differential Privacy and Analytical Moments Accountant AISTATS 2019
Model Consistency for Learning with Mirror-Stratifiable Regularizers AISTATS 2019
Detection of Planted Solutions for Flat Satisfiability Problems AISTATS 2019
Towards Clustering High-dimensional Gaussian Mixture Clouds in Linear Running Time AISTATS 2019
Black Box Quantiles for Kernel Learning AISTATS 2019
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit AISTATS 2019
Sample Complexity of Sinkhorn Divergences AISTATS 2019
Does data interpolation contradict statistical optimality? AISTATS 2019
A Family of Exact Goodness-of-Fit Tests for High-Dimensional Discrete Distributions AISTATS 2019
Statistical Learning under Nonstationary Mixing Processes AISTATS 2019
Lifted Weight Learning of Markov Logic Networks Revisited AISTATS 2019
Causal Discovery in the Presence of Missing Data AISTATS 2019
Learning Tree Structures from Noisy Data AISTATS 2019
Sharp Analysis of Learning with Discrete Losses AISTATS 2019
Test without Trust: Optimal Locally Private Distribution Testing AISTATS 2019
The non-parametric bootstrap and spectral analysis in moderate and high-dimension AISTATS 2019
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization AISTATS 2019
Least Squares Estimation of Weakly Convex Functions AISTATS 2019
Kernel Exponential Family Estimation via Doubly Dual Embedding AISTATS 2019