Greedy Strategies for Convex Optimization
  We investigate two greedy strategies for finding an approximation to the minimum of a convex function $E$ defined on a Hilbert space $H$. We prove convergence rates for these algorithms under suitable conditions on the objective function $E$. These conditions involve the behavior of the modulus of smoothness and the modulus of uniform convexity of $E$. 
Hao Nguyen and Guergana Petrova
math.NA