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, 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.

翻译：本文提出\textit{GO4Align}，一种通过显式对齐多任务间优化过程以解决任务失衡问题的多任务优化方法。为实现这一目标，我们设计了一种自适应组风险最小化策略，该策略在实现上包含两项技术：(i) 动态分组分配，基于任务间交互对相似任务进行聚类；(ii) 风险引导的组指示器，利用历史迭代中的风险信息挖掘一致的任务相关性。在多样化基准测试上的综合实验结果表明，本方法在取得更优性能的同时，计算成本反而更低。