Berkeley Method of Deterministic Annealing

The Berkeley Method of Deterministic Annealing is an optimization technique that finds optimal solutions by gradually reducing a "temperature" parameter, inspired by the cooling process in nature. It begins with a broad, flexible search where many possibilities are considered widely. As the temperature decreases, the method refines the search, focusing more tightly on promising options. This process helps to avoid local minima—suboptimal solutions—leading to better overall results. It’s widely used for clustering and pattern recognition tasks, balancing exploration and exploitation to systematically arrive at high-quality solutions.