Practical Solutions and Value of LibMOON: A Gradient-Based Multiobjective Optimization Library for Large-Scale Machine Learning
Introduction
Multiobjective optimization (MOO) is crucial in machine learning, addressing trade-offs between performance metrics in real-world applications like robotics, fair classification, and recommendation systems.
Challenges in Multiobjective Optimization
Scalable methods are needed to handle large models efficiently, especially for deep neural networks. Traditional approaches struggle with large-scale machine-learning problems, leading to increased computational burden.
Current Methods and Limitations
Existing methods rely on evolutionary algorithms but are limited by their zeroth-order nature, making them less suitable for modern machine-learning tasks.
Introducing LibMOON
LibMOON is a new library that provides a gradient-based multiobjective optimization framework, designed to optimize large-scale machine-learning models more effectively than previous methods. It supports over twenty cutting-edge optimization methods and offers GPU acceleration.
Core Functionality of LibMOON
LibMOON’s functionality lies in its three categories of solvers: Multiobjective optimization solvers (MOO), Pareto set learning solvers (PSL), and multiobjective Bayesian optimization solvers (MOBO). Each category is modular and allows for easy integration of new methods, making LibMOON highly adaptable.
Performance and Applications
LibMOON’s gradient-based solvers achieved better hypervolume scores than traditional evolutionary approaches, demonstrating superior ability to explore the solution space. The library also outperformed existing methods in real-world applications like fairness classification and multiobjective machine learning tasks.
Conclusion
LibMOON introduces a robust, gradient-based solution to multiobjective optimization, addressing the key limitations of existing methods. Its ability to efficiently scale to large machine learning models and provide accurate Pareto sets makes it an essential tool for researchers in machine learning.
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