A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
New method uses rank-conditioned Horvitz-Thompson estimation for unbiased sample reuse in Plackett-Luce best-of-K objective.
Subsampling reduces computational cost in supervised learning in reproducing kernel Hilbert spaces.
With a growing interest in using non-representative samples to train prediction models for numerous outcomes it is necessary to account for the sampling design that gives rise to the data in order to assess the generalized predictive utility of a proposed prediction rule. After learning a prediction rule based on a non…
Applied researchers often construct a network from a random sample of nodes in order to infer properties of the parent network. Two of the most widely used sampling schemes are subgraph sampling, where we sample each vertex independently with probability and observe the subgraph induced by the sampled vertices, and…
PPI uses predictions and weighting to infer from partially labeled data.
DN estimator mitigates network interference in experiments.
This paper reviews various sampling methods from statistics and machine learning.