60 citations · 203 across the 23 of their papers we have counts for
23 papers
Stochastic Nested Compositional Bi-level Optimization for Robust Feature Learning
Xuxing Chen, Krishnakumar Balasubramanian, Saeed Ghadimi
We develop and analyze stochastic approximation algorithms for solving nested compositional bi-level optimization problems. These problems involve a nested composition of poten…
A One-Sample Decentralized Proximal Algorithm for Non-Convex Stochastic Composite Optimization
Tesi Xiao, Xuxing Chen, Krishnakumar Balasubramanian +1
We focus on decentralized stochastic non-convex optimization, where agents work together to optimize a composite objective function which is a sum of a smooth term and a non-sm…
Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data
Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi
We study stochastic optimization algorithms for constrained nonconvex stochastic optimization problems with Markovian data. In particular, we focus on the case when the transition…
RIGID: Robust Linear Regression with Missing Data
Alireza Aghasi, MohammadJavad Feizollahi, Saeed Ghadimi
We present a robust framework to perform linear regression with missing entries in the features. By considering an elliptical data distribution, and specifically a multivariate nor…
Stochastic Search for a Parametric Cost Function Approximation: Energy storage with rolling forecasts
Saeed Ghadimi, Warren B. Powell
Rolling forecasts have been almost overlooked in the renewable energy storage literature. In this paper, we provide a new approach for handling uncertainty not just in the accuracy…
A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization
Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi
We propose a projection-free conditional gradient-type algorithm for smooth stochastic multi-level composition optimization, where the objective function is a nested composition of…