← Learning Types
Machine Learning › Learning Types ›

Statistical Learning

65 directly classified papers

Papers per year

Papers

On the Power of Differentiable Learning versus PAC and SQ Learning NIPS 2021
Analysis of Sensing Spectral for Signal Recovery under a Generalized Linear Model NIPS 2021
Statistical Undecidability in Linear, Non-Gaussian Causal Models in the Presence of Latent Confounders NIPS 2021
Distributionally Robust Parametric Maximum Likelihood Estimation NIPS 2020
The All-or-Nothing Phenomenon in Sparse Tensor PCA NIPS 2020
Information theoretic limits of learning a sparse rule NIPS 2020
Estimation of Skill Distribution from a Tournament NIPS 2020
Statistical Guarantees of Distributed Nearest Neighbor Classification NIPS 2020
Agnostic Learning of a Single Neuron with Gradient Descent NIPS 2020
Sequential Mode Estimation with Oracle Queries AAAI 2020
The Rationality of Semantic Change ACL 2019
Causal Discovery in the Presence of Missing Data AISTATS 2019
Unified Sample-Optimal Property Estimation in Near-Linear Time NIPS 2019
ADDIS: an adaptive discarding algorithm for online FDR control with conservative nulls NIPS 2019
Surface Realization Shared Task 2018 (SR18): The Tilburg University Approach ACL 2018
Early Stopping for Nonparametric Testing NIPS 2018
Scaling the Poisson GLM to massive neural datasets through polynomial approximations NIPS 2018
Data Amplification: A Unified and Competitive Approach to Property Estimation NIPS 2018
Independence clustering (without a matrix) NIPS 2017
The power of absolute discounting: all-dimensional distribution estimation NIPS 2017
On the Complexity of Learning Neural Networks NIPS 2017
Learning from Survey Training Samples: Rate Bounds for Horvitz-Thompson Risk Minimizers ACML 2016
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning NIPS 2016
Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences NIPS 2016
Fast Two-Sample Testing with Analytic Representations of Probability Measures NIPS 2015