GO4Align: Group Optimization for Multi-Task Alignment
Jiayi Shen Cheems Wang Zehao Xiao Nanne Van Noord Marcel Worring
This paper proposes \textit{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,
compromising two crucial 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 typical benchmarks demonstrate our method's performance superiority
with even lower computational costs.