Swiss Optimization Symposium

The workshop aims to chart the next frontier of optimization, a field driving transformative advances in machine learning, artificial intelligence, and complex decision-making. This symposium will cover several rapidly growing themes critical to the future of optimization:

1. Optimization for Reinforcement Learning (RL) and Games, to address modern decision-making in dynamic environments and multi-agent systems;
2. Algorithm Design Automation, to explore computer-aided analysis and data-driven algorithm design tailored for specific problem structures;
3. Optimization in the Era of Large Language Models (LLM), to tackle modern challenges in training and fine-tuning of language models at scale;
4. Tuning-Free Optimization, to improve the adaptivity and usability of optimization algorithms in practice;
5. Geometry-Aware Optimization, to extend optimization beyond traditional Euclidean spaces such as probability spaces, manifolds, and other geometries.

Bringing together leading researchers and industry experts, we aim to foster collaboration, spark innovative ideas, and address the emerging challenges shaping the future of optimization. The symposium will be a catalyst for pioneering research that will drive the next wave of advancements in AI, machine learning, and beyond, ensuring that optimization remains at the forefront of technological progress.