2 papers
cs.LG2026
Momba: Network Modernization Improves Multi-Objective Reinforcement Learning
Adam Štafa, Santeri Heiskanen, Petr Novotný +1
Recent advances in deep reinforcement learning (RL) have shown that improving neural network architectures can yield substantial gains in sample efficiency and asymptotic performan…
cs.LG2026
Pareto-Conditioned Diffusion Models for Offline Multi-Objective Optimization
Jatan Shrestha, Santeri Heiskanen, Kari Hepola +3
Multi-objective optimization (MOO) arises in many real-world applications where trade-offs between competing objectives must be carefully balanced. In the offline setting, where on…