GO4Align: Group Optimization for Multi-Task Alignment

Open Access
Authors
Publication date 2025
Host editors
  • A. Globerson
  • L. Mackey
  • D. Belgrave
  • A. Fan
  • U. Paquet
  • J. Tomczak
  • C. Zhang
Book title 38th Conference on Neural Information Processing Systems (NeurIPS 2024)
Book subtitle 10-15 December 2024, Vancouver, Canada
ISBN (electronic)
  • 9798331314385
Series Advances in Neural Information Processing Systems
Event 38th Conference on Neural Information Processing Systems, NeurIPS 2024
Pages (from-to) 111382-111405
Publisher Neural Information Processing Systems Foundation
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract

This paper proposes GO4Align, a multi-task optimization approach that tackles task imbalance by explicitly aligning the optimization across tasks. To achieve this, we design an adaptive group risk minimization strategy, comprising two techniques in implementation: (i) dynamical group assignment, which clusters similar tasks based on task interactions; (ii) risk-guided group indicators, which exploit consistent task correlations with risk information from previous iterations. Comprehensive experimental results on diverse benchmarks demonstrate our method's performance superiority with even lower computational costs.

Document type Conference contribution
Language English
Published at
https://doi.org/10.52202/079017-3537 (Final published version)
Published at
Other links
Downloads
079017-3537open (Final published version)
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