Group recovery after trimming, and level-free flagging, in robust clusterwise regression

arXiv:2609.31019 · stat.CO, stat.ME, stat.ML · Submitted 2026-09-25 · Read on arXiv

stat.CO, stat.ME, stat.ML

Submitted: 2026-09-25

Updated: 2026-10-01

Code: https://github.com/sorujov/eesp

Terminology

• Accuracy — 35× in this paper · explained in 1 episode
• Clustering — 13× in this paper · explained in 2 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Alternation — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Admissibility — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Heteroscedasticity — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes

Sources

• Component-wise Adaptive Trimming For Robust Mixture Regression

Related papers

• A fast non-reversible sampler for Bayesian mixture models
• BKP: An R Package for Beta Kernel Process Modeling
• Amortized quadrature for posterior expectations in inverse problems
• A Non-asymptotic Analysis for Learning and Applying a Preconditioner in MCMC
• Prob-GParareal: A Probabilistic Numerical Parallel-in-Time Solver for Differential Equations
• Statistical Taylor Expansion: A New and Path-Independent Method for Uncertainty Analysis