---
OA_place: publisher
_id: '68'
abstract:
- lang: eng
  text: The most common assumption made in statistical learning theory is the assumption
    of the independent and identically distributed (i.i.d.) data. While being very
    convenient mathematically, it is often very clearly violated in practice. This
    disparity between the machine learning theory and applications underlies a growing
    demand in the development of algorithms that learn from dependent data and theory
    that can provide generalization guarantees similar to the independent situations.
    This thesis is dedicated to two variants of dependencies that can arise in practice.
    One is a dependence on the level of samples in a single learning task. Another
    dependency type arises in the multi-task setting when the tasks are dependent
    on each other even though the data for them can be i.i.d. In both cases we model
    the data (samples or tasks) as stochastic processes and introduce new algorithms
    for both settings that take into account and exploit the resulting dependencies.
    We prove the theoretical guarantees on the performance of the introduced algorithms
    under different evaluation criteria and, in addition, we compliment the theoretical
    study by the empirical one, where we evaluate some of the algorithms on two real
    world datasets to highlight their practical applicability.
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Alexander
  full_name: Zimin, Alexander
  id: 37099E9C-F248-11E8-B48F-1D18A9856A87
  last_name: Zimin
citation:
  ama: Zimin A. Learning from dependent data. 2018. doi:<a href="https://doi.org/10.15479/AT:ISTA:TH1048">10.15479/AT:ISTA:TH1048</a>
  apa: Zimin, A. (2018). <i>Learning from dependent data</i>. Institute of Science
    and Technology Austria. <a href="https://doi.org/10.15479/AT:ISTA:TH1048">https://doi.org/10.15479/AT:ISTA:TH1048</a>
  chicago: Zimin, Alexander. “Learning from Dependent Data.” Institute of Science
    and Technology Austria, 2018. <a href="https://doi.org/10.15479/AT:ISTA:TH1048">https://doi.org/10.15479/AT:ISTA:TH1048</a>.
  ieee: A. Zimin, “Learning from dependent data,” Institute of Science and Technology
    Austria, 2018.
  ista: Zimin A. 2018. Learning from dependent data. Institute of Science and Technology
    Austria.
  mla: Zimin, Alexander. <i>Learning from Dependent Data</i>. Institute of Science
    and Technology Austria, 2018, doi:<a href="https://doi.org/10.15479/AT:ISTA:TH1048">10.15479/AT:ISTA:TH1048</a>.
  short: A. Zimin, Learning from Dependent Data, Institute of Science and Technology
    Austria, 2018.
corr_author: '1'
date_created: 2018-12-11T11:44:27Z
date_published: 2018-09-01T00:00:00Z
date_updated: 2026-07-29T13:31:12Z
day: '01'
ddc:
- '004'
- '519'
degree_awarded: PhD
department:
- _id: ChLa
- _id: GradSch
doi: 10.15479/AT:ISTA:TH1048
doi_confirm: '1'
ec_funded: 1
file:
- access_level: open_access
  checksum: e849dd40a915e4d6c5572b51b517f098
  content_type: application/pdf
  creator: dernst
  date_created: 2019-04-09T07:32:47Z
  date_updated: 2020-07-14T12:47:40Z
  file_id: '6253'
  file_name: 2018_Thesis_Zimin.pdf
  file_size: 1036137
  relation: main_file
- access_level: closed
  checksum: da092153cec55c97461bd53c45c5d139
  content_type: application/zip
  creator: dernst
  date_created: 2019-04-09T07:32:47Z
  date_updated: 2020-07-14T12:47:40Z
  file_id: '6254'
  file_name: 2018_Thesis_Zimin_Source.zip
  file_size: 637490
  relation: source_file
file_date_updated: 2020-07-14T12:47:40Z
has_accepted_license: '1'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: '92'
project:
- _id: 2532554C-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '308036'
  name: Lifelong Learning of Visual Scene Understanding
publication_identifier:
  issn:
  - 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
publist_id: '7986'
pubrep_id: '1048'
status: public
supervisor:
- first_name: Christoph
  full_name: Lampert, Christoph
  id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
  last_name: Lampert
  orcid: 0000-0001-8622-7887
title: Learning from dependent data
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2018'
...