← Core Methods
Machine Learning › Core Methods ›

Statistical Learning

11 directly classified papers

Papers per year

Papers

Don’t Sweat the Small Stuff: Segment-Level Meta-Evaluation Based on Pairwise Difference Correlation EMNLP 2025
VEC-SBM: Optimal Community Detection with Vectorial Edges Covariates AISTATS 2024
Identifying Selection Bias from Observational Data AAAI 2023
A Fourier Approach to Mixture Learning NIPS 2022
List-Decodable Mean Estimation via Iterative Multi-Filtering NIPS 2020
SURF: A Simple, Universal, Robust, Fast Distribution Learning Algorithm NIPS 2020
Scaling Hidden Markov Language Models EMNLP 2020
A comparison of statistical association measures for identifying dependency-based collocations in various languages. ACL 2019
Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators NIPS 2016
Fast Algorithms for Gaussian Noise Invariant Independent Component Analysis NIPS 2013
Multi-Task Averaging NIPS 2012