نسخة أولية وصول مفتوح
Hamiltonian Metric Learning and Energy-Based Training: A Dissipative Geometric Framework for Optimization
Optimization in machine learning is usually expressed through iterative rules that update model parameters using information from the loss landscape. In this work, we study an alternative viewpoint in which parameter optimization is treated as the evolution of a dissipative dynamical system. The model parameters are re …