A General Greedy Approximation Algorithm with Applications

Part of Advances in Neural Information Processing Systems 14 (NIPS 2001)

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T. Zhang


Greedy approximation algorithms have been frequently used to obtain sparse solutions to learning problems. In this paper, we present a general greedy algorithm for solving a class of convex optimization problems. We derive a bound on the rate of approximation for this algorithm, and show that our algorithm includes a number of earlier studies as special cases.