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What is Mirror Descent and Variable Metric Methods about?
1. Mirror descent is a generalization of projected subgradient descent that replaces the Euclidean norm with a Bregman divergence. This allows the use of different distance-like functions. 2. The convergence rate of projected subgradient descent depends on the boundedness of subgradients and initialization radius. Mirror descent enjoys similar convergence guarantees by exploiting properties of Bregman divergences like strong convexity. 3. Standard setups for mirror descent include using the squared Euclide
- Author
- myturtle game01
- Language
- EN