Optimization
Pre-Trained Multi-Goal Transformers with Prompt Optimization for Efficient Online Adaptation
We adopt a multi-armed bandit framework for this process, enhancing prompt selection based on the returns from online trajectories.
Federated Multi-Objective Learning
In recent years, multi-objective optimization (MOO) emerges as a foundational problem underpinning many multi-agent multi-task learning applications.
Achieving O (ฯต 1. 5) Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization
This class of bilevel problems has been studied extensively from the theoretical perspective in recent years.
CP-SLAM: Collaborative Neural Point-based SLAM
A novel global optimization framework is also proposed to improve the system accuracy like traditional bundle adjustment.
