Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning

1. 1Formulate the multi-objective problem using Tchebycheff scalarization
2. 2Apply Adaptive Online Mirror Descent to optimize the scalarized objective
3. 3Update the optimization process adaptively based on user feedback or performance metrics
4. 4Analyze the trade-offs between objectives and adjust the optimization process accordingly

Machine learning researchers and engineers on a team can benefit from this approach as it allows for more flexible and efficient optimization of multiple objectives, while product managers can use it to make informed decisions about trade-offs

💡 Tchebycheff scalarization allows for locating solutions with user-specified trade-offs, and Adaptive Online Mirror Descent provides an efficient optimization method

💡 Adaptive Online Mirror Descent for multi-objective learning with Tchebycheff scalarization!