GO4Align: Group Optimization for Multi-Task Alignment
| Authors | |
|---|---|
| Publication date | 2025 |
| Host editors |
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| Book title | 38th Conference on Neural Information Processing Systems (NeurIPS 2024) |
| Book subtitle | 10-15 December 2024, Vancouver, Canada |
| ISBN (electronic) |
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| 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 |
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| 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 |
https://papers.nips.cc/paper_files/paper/2024/hash/c98987c5ec4f30920d7190dc699e3daf-Abstract-Conference.html
(Accepted author manuscript)
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| Other links | |
| Downloads |
NeurIPS-2024-go4align-group-optimization-for-multi-task-alignment-Paper-Conference
(Accepted author manuscript)
079017-3537open
(Final published version)
|
| Permalink to this page | |
