---
OA_place: publisher
OA_type: free access
_id: '22824'
abstract:
- lang: eng
  text: "We present new fast-rate PAC-Bayesian generalization bounds for multi-task
    and\r\nmeta-learning in the unbalanced setting, i.e. when the tasks have training
    sets of\r\ndifferent sizes, as is typically the case in real-world scenarios.
    Previously, only\r\nstandard-rate bounds were known for this situation, while
    fast-rate bounds were\r\nlimited to the setting where all training sets are of
    equal size. Our new bounds\r\nare numerically computable as well as interpretable,
    and we demonstrate their\r\nflexibility in handling a number of cases where they
    give stronger guarantees\r\nthan previous bounds. Besides the bounds themselves,
    we also make conceptual\r\ncontributions: we demonstrate that the unbalanced multi-task
    setting has different\r\nstatistical properties than the balanced situation, specifically
    that proofs from\r\nthe balanced situation do not carry over to the unbalanced
    setting. Additionally,\r\nwe shed light on the fact that the unbalanced situation
    allows two meaningful\r\ndefinitions of multi-task risk, depending on whether
    all tasks should be considered\r\nequally important or if sample-rich tasks should
    receive more weight than samplepoor ones."
acknowledged_ssus:
- _id: ScienComp
acknowledgement: This research was supported by the Scientific Service Units (SSU)
  of ISTA through resources provided by Scientific Computing (SciComp).
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
author:
- first_name: Hossein
  full_name: Zakerinia, Hossein
  id: 653bd8b6-f394-11eb-9cf6-c0bbf6cd78d4
  last_name: Zakerinia
  orcid: 0009-0007-3977-6462
- first_name: Christoph
  full_name: Lampert, Christoph
  id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
  last_name: Lampert
  orcid: 0000-0001-8622-7887
citation:
  ama: 'Zakerinia H, Lampert C. Fast rate bounds for multi-task and meta-learning
    with different sample sizes. In: <i>39th Conference on Neural Information Processing
    Systems</i>. Vol 38. Neural Information Processing Systems Foundation; 2025:9062-9093.
    doi:<a href="https://doi.org/10.52202/085713-0278">10.52202/085713-0278</a>'
  apa: 'Zakerinia, H., &#38; Lampert, C. (2025). Fast rate bounds for multi-task and
    meta-learning with different sample sizes. In <i>39th Conference on Neural Information
    Processing Systems</i> (Vol. 38, pp. 9062–9093). San Diego, CA, United States:
    Neural Information Processing Systems Foundation. <a href="https://doi.org/10.52202/085713-0278">https://doi.org/10.52202/085713-0278</a>'
  chicago: Zakerinia, Hossein, and Christoph Lampert. “Fast Rate Bounds for Multi-Task
    and Meta-Learning with Different Sample Sizes.” In <i>39th Conference on Neural
    Information Processing Systems</i>, 38:9062–93. Neural Information Processing
    Systems Foundation, 2025. <a href="https://doi.org/10.52202/085713-0278">https://doi.org/10.52202/085713-0278</a>.
  ieee: H. Zakerinia and C. Lampert, “Fast rate bounds for multi-task and meta-learning
    with different sample sizes,” in <i>39th Conference on Neural Information Processing
    Systems</i>, San Diego, CA, United States, 2025, vol. 38, pp. 9062–9093.
  ista: 'Zakerinia H, Lampert C. 2025. Fast rate bounds for multi-task and meta-learning
    with different sample sizes. 39th Conference on Neural Information Processing
    Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information
    Processing Systems, vol. 38, 9062–9093.'
  mla: Zakerinia, Hossein, and Christoph Lampert. “Fast Rate Bounds for Multi-Task
    and Meta-Learning with Different Sample Sizes.” <i>39th Conference on Neural Information
    Processing Systems</i>, vol. 38, Neural Information Processing Systems Foundation,
    2025, pp. 9062–93, doi:<a href="https://doi.org/10.52202/085713-0278">10.52202/085713-0278</a>.
  short: H. Zakerinia, C. Lampert, in:, 39th Conference on Neural Information Processing
    Systems, Neural Information Processing Systems Foundation, 2025, pp. 9062–9093.
conference:
  end_date: 2025-12-07
  location: San Diego, CA, United States
  name: 'NeurIPS: Neural Information Processing Systems'
  start_date: 2025-12-02
corr_author: '1'
das_tickbox: '0'
date_created: 2026-09-06T22:01:59Z
date_published: 2025-12-02T00:00:00Z
date_updated: 2026-09-10T08:37:33Z
day: '02'
department:
- _id: GradSch
- _id: ChLa
doi: 10.52202/085713-0278
fulldoi: https://doi.org/10.52202/085713-0278
intvolume: '        38'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.52202/085713-0278
month: '12'
oa: 1
oa_version: Published Version
page: 9062-9093
publication: 39th Conference on Neural Information Processing Systems
publication_identifier:
  isbn:
  - '9798331338275'
  issn:
  - 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: yes
title: Fast rate bounds for multi-task and meta-learning with different sample sizes
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 38
year: '2025'
...