111 citations · 338 across the 50 of their papers we have counts for
11 papers · 1 filter
A Primal-Dual Framework for Decentralized Stochastic Optimization
Ketan Rajawat, Chirag Kumar
We consider the decentralized convex optimization problem, where multiple agents must cooperatively minimize a cumulative objective function, with each local function expressible a…
Stochastic Compositional Gradient Descent under Compositional Constraints
Srujan Teja Thomdapu, Harshvardhan, Ketan Rajawat
This work studies constrained stochastic optimization problems where the objective and constraint functions are convex and expressed as compositions of stochastic functions. The pr…
Distributed Optimisation With Communication Delays
Shuubham Ojha, Ketan Rajawat
This paper discusses distributed optimization over a directed graph. We begin with some well known algorithms which achieve consensus among agents including FROST [1], which posses…
Sparse Representations of Positive Functions via First and Second-Order Pseudo-Mirror Descent
Abhishek Chakraborty, Ketan Rajawat, Alec Koppel
We consider expected risk minimization problems when the range of the estimator is required to be nonnegative, motivated by the settings of maximum likelihood estimation (MLE) and…
Practical Precoding via Asynchronous Stochastic Successive Convex Approximation
Basil M. Idrees, Javed Akhtar, Ketan Rajawat
We consider stochastic optimization of a smooth non-convex loss function with a convex non-smooth regularizer. In the online setting, where a single sample of the stochastic gradie…
Conservative Stochastic Optimization with Expectation Constraints
Zeeshan Akhtar, Amrit Singh Bedi, Ketan Rajawat
This paper considers stochastic convex optimization problems where the objective and constraint functions involve expectations with respect to the data indices or environmental var…