6 citations · 18 across the 11 of their papers we have counts for
6 papers · 1 filter
Sample average approximation with heavier tails II: localization in stochastic convex optimization and persistence results for the Lasso
Roberto I. Oliveira, Philip Thompson
``Localization'' has proven to be a valuable tool in the Statistical Learning literature as it allows sharp risk bounds in terms of the problem geometry. Localized bounds seem to b…
On variance reduction for stochastic smooth convex optimization with multiplicative noise
Alejandro Jofré, Philip Thompson
We propose dynamic sampled stochastic approximation (SA) methods for stochastic optimization with a heavy-tailed distribution (with finite 2nd moment). The objective is the sum of…
Sample average approximation with heavier tails I: non-asymptotic bounds with weak assumptions and stochastic constraints
Roberto I. Oliveira, Philip Thompson
We derive new and improved non-asymptotic deviation inequalities for the sample average approximation (SAA) of an optimization problem. Our results give strong error probability bo…
Incremental constraint projection methods for monotone stochastic variational inequalities
Alfredo Iusem, Alejandro Jofré, Philip Thompson
We consider stochastic variational inequalities with monotone operators defined as the expected value of a random operator. We assume the feasible set is the intersection of a larg…
Variance-based stochastic extragradient methods with line search for stochastic variational inequalities
Alfredo Iusem, Alejandro Jofré, Roberto I. Oliveira +1
A dynamic sampled stochastic approximated (DS-SA) extragradient method for stochastic variational inequalities (SVI) is proposed that is \emph{robust} with respect to an unknown Li…
Extragradient method with variance reduction for stochastic variational inequalities
Alfredo Iusem, Alejandro Jofré, Roberto I. Oliveira +1
We propose an extragradient method with stepsizes bounded away from zero for stochastic variational inequalities requiring only pseudo-monotonicity. We provide convergence and comp…