2010 Research Summary
Stochastic Approximation in the presence of heavy-tailed and long-range-dependent noise
View Current Project Information
Venkat Anantharam and Vivek Borkar1
ONR/MURI
The theory of stochastic approximation is widely used to develop algorithms convergent to global optima under noisy measurements. Typically the noise is modeled as a Brownian motion or other short range dependent process. In networks with long-range-dependent traffic, such noise models are inadequate. We are developing a theory of stochastic approximation that is broader in scope and can include heavy-tailed and long-range-dependent noise in the measurements.
1TIFR, Mumbai