mlsanityData to 14 Oct 2026

Performance of Distribution Regression with Doubling Measure under the seek of Closest Point

arXiv 2203.00155 ↗First posted 1 Mar 2022cs.LG math.ST stat.THcited by 2

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Abstract (arXiv)

We study the distribution regression problem assuming the distribution of distributions has a doubling measure larger than one. First, we explore the geometry of any distributions that has doubling measure larger than one and build a small theory around it. Then, we show how to utilize this theory to find one of the nearest distributions adaptively and compute the regression value based on these distributions. Finally, we provide the accuracy of the suggested method here and provide the theoretical analysis for it.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 4 of its 16 references that are in the map. First posted on arXiv 1 Mar 2022.

Builds on

4 of 16 references.

References · 4

  1. 2013Distribution-Free Distribution Regressioncited by 21
  2. 2013Low-Rank Matrix and Tensor Completion via Adaptive Samplingcited by 19
  3. 2021An Ambient Intelligence-Based Human Behavior Monitoring Framework for Ubiquitous Environmentscited by 5
  4. 2020Adaptive Sampling Distributed Stochastic Variance Reduced Gradient for Heterogeneous Distributed Datasetscited by 4

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Cited by year

Citing papers per year: 2022: 2.

2 papers.

  1. 2022Lifelong Matrix Completion with Sparsity-Numbercited by 4
  2. 2022Adaptive Noisy Matrix Completioncited by 3