Noise Conditions for Prespecified Convergence Rates of Stochastic Approximation Algorithms.
Edwin K. P. ChongI-Jeng WangSanjeev R. KulkarniPublished in: IEEE Trans. Inf. Theory (1999)
Keyphrases
- approximation algorithms
- convergence rate
- primal dual
- approximation schemes
- np hard
- special case
- vertex cover
- learning rate
- worst case
- sufficient conditions
- minimum cost
- set cover
- global convergence
- approximation ratio
- randomized algorithms
- undirected graph
- linear programming
- precedence constraints
- stopping criterion
- constant factor
- gaussian kernels
- genetic algorithm
- greedy algorithm
- numerical stability
- polynomial time approximation
- lower bound