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20182022
most citedAccelerated, Optimal, and Parallel: Some Results on Model-Based Stochastic Optimization

5 citations · 6 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG20221 cited

Private optimization in the interpolation regime: faster rates and hardness results

Hilal Asi, Karan Chadha, Gary Cheng +1

In non-private stochastic convex optimization, stochastic gradient methods converge much faster on interpolation problems -- problems where there exists a solution that simultaneou…

math.OC20215 cited

Accelerated, Optimal, and Parallel: Some Results on Model-Based Stochastic Optimization

Karan Chadha, Gary Cheng, John C. Duchi

We extend the Approximate-Proximal Point (aProx) family of model-based methods for solving stochastic convex optimization problems, including stochastic subgradient, proximal point…

math.OC2019

Efficiency Fairness Tradeoff in Battery Sharing

Karan N. Chadha, Ankur A. Kulkarni, Jayakrishnan Nair

The increasing presence of decentralized renewable generation in the power grid has motivated consumers to install batteries to save excess energy for future use. The high price of…

cs.GT2019

Aggregate Play and Welfare in Strategic Interactions on Networks

Karan N. Chadha, Ankur A. Kulkarni

In recent work by Bramoullé and Kranton, a model for the provision of public goods on a network was presented and relations between equilibria of such a game and properties of the…

cs.DM2018

On Independent Cliques and Linear Complementarity Problems

Karan N. Chadha, Ankur A. Kulkarni

In recent work (Pandit and Kulkarni [Discrete Applied Mathematics, 244 (2018), pp. 155--169]), the independence number of a graph was characterized as the maximum of the n…