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Statistical Learning

4,117 papers

Papers per year

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Papers

Optimal Quantum Sample Complexity of Learning Algorithms JMLR 2018
Online Bootstrap Confidence Intervals for the Stochastic Gradient Descent Estimator JMLR 2018
LHD: Improving Cache Hit Rate by Maximizing Hit Density NSDI 2018
Deepview: Virtual Disk Failure Diagnosis and Pattern Detection for Azure NSDI 2018
Model-Powered Conditional Independence Test NIPS 2017
FALKON: An Optimal Large Scale Kernel Method NIPS 2017
Minimax Estimation of Bandable Precision Matrices NIPS 2017
Estimation of the covariance structure of heavy-tailed distributions NIPS 2017
A Universal Analysis of Large-Scale Regularized Least Squares Solutions NIPS 2017
Expectation Propagation for t-Exponential Family Using q-Algebra NIPS 2017
On Tensor Train Rank Minimization : Statistical Efficiency and Scalable Algorithm NIPS 2017
Recycling Privileged Learning and Distribution Matching for Fairness NIPS 2017
Population Matching Discrepancy and Applications in Deep Learning NIPS 2017
Statistical Cost Sharing NIPS 2017
The power of absolute discounting: all-dimensional distribution estimation NIPS 2017
Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting NIPS 2017
Independence clustering (without a matrix) NIPS 2017
Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods NIPS 2017
Robust Conditional Probabilities NIPS 2017
Sample and Computationally Efficient Learning Algorithms under S-Concave Distributions NIPS 2017
Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma NIPS 2017
On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models NIPS 2017
Unbiased estimates for linear regression via volume sampling NIPS 2017
Variable Importance Using Decision Trees NIPS 2017
Variance-based Regularization with Convex Objectives NIPS 2017