Seminar: Henrik Imberg, Univeristy of Gothenburg

Seminar

Date: Wednesday 18 December 2024

Time: 13.00 – 14.00

Location: Campus Albano, lecture room 29, house 4, level 2

Active sampling: A machine-learning-assisted framework for finite population inference with optimal subsamples

Abstract

Data subsampling has become widely recognized as a tool to overcome computational and economic bottlenecks in analyzing massive datasets. We contribute to the development of adaptive design for estimation of finite population characteristics, using active learning and adaptive importance sampling. We propose an active sampling strategy that iterates between estimation and data collection with optimal subsamples, guided by machine learning predictions on yet unseen data. The method is illustrated on virtual simulation-based safety assessment of advanced driver assistance systems. Substantial performance improvements are demonstrated compared to traditional sampling methods. The presentation is based on our recent Technometrics paper, published in 2024, available at: https://doi.org/10.1080/00401706.2024.2374554

Theme

Mathematics and Statistics

Last updated: December 13, 2024

Source: Department of Statistics

eventNewsArticle

standard-article

true

{
  "dimensions": [
    {
      "id": "department.categorydimension.subject",
      "name": "Global categories",
      "enumerable": true,
      "entities": [],
      "localizations": {}
    },
    {
      "id": "department.categorydimension.tag.Keywords",
      "name": "Keywords",
      "enumerable": false,
      "entities": [],
      "localizations": {}
    },
    {
      "id": "department.categorydimension.tag.Person",
      "name": "Person",
      "enumerable": false,
      "entities": [],
      "localizations": {}
    },
    {
      "id": "department.categorydimension.tag.Tag",
      "name": "Tag",
      "enumerable": false,
      "entities": [],
      "localizations": {}
    },
    {
      "id": "Statistiska.eng.lokala.kat",
      "name": "Lokala kategorier ENG Statistiska",
      "enumerable": true,
      "entities": [
        {
          "id": "Statistiska.eng.lokala.kat.kal",
          "name": "Local calendar",
          "entities": [],
          "attributes": [],
          "childrenOmitted": false,
          "localizations": {}
        },
        {
          "id": "Statistiska.eng.lokala.kat.kal",
          "name": "Local calendar",
          "entities": [
            {
              "id": "Statistiska.eng.lokala.kat.kal.fo",
              "name": "Research",
              "entities": [],
              "attributes": [],
              "childrenOmitted": false,
              "localizations": {}
            }
          ],
          "attributes": [],
          "childrenOmitted": false,
          "localizations": {}
        }
      ],
      "localizations": {}
    },
    {
      "id": "webb2021.categorydimension.Category.Events",
      "name": "Globala kategorier Kalender (Webb 2021)",
      "enumerable": true,
      "entities": [],
      "localizations": {}
    },
    {
      "id": "webb2021.categorydimension.Label",
      "name": "Tema (Webb 2021)",
      "enumerable": true,
      "entities": [],
      "localizations": {}
    },
    {
      "id": "webb2021.categorydimension.Label.en",
      "name": "Themes (Webb 2021)",
      "enumerable": true,
      "entities": [
        {
          "id": "webb2021.categorydimension.Label.en.Maths",
          "name": "Mathematics and Statistics",
          "entities": [],
          "attributes": [],
          "childrenOmitted": false,
          "localizations": {}
        }
      ],
      "localizations": {}
    },
    {
      "id": "webb2021.categorydimension.Keyword",
      "name": "Keywords (Webb 2021)",
      "enumerable": false,
      "entities": [],
      "localizations": {}
    }
  ]
}