5 citations · 13 across the 5 of their papers we have counts for
6 papers
Approximating APS under Submodular and XOS valuations with Binary Marginals
Pooja Kulkarni, Rucha Kulkarni, Ruta Mehta
We study the problem of fairly dividing indivisible goods among a set of agents under the fairness notion of Any Price Share (APS). APS is known to dominate the widely studied Maxi…
1/2 Approximate MMS Allocation for Separable Piecewise Linear Concave Valuations
Chandra Chekuri, Pooja Kulkarni, Rucha Kulkarni +1
We study fair distribution of a collection of m indivisible goods among a group of n agents, using the widely recognized fairness principles of Maximin Share (MMS) and Any Price Sh…
Dynamic Data-Race Detection through the Fine-Grained Lens
Rucha Kulkarni, Umang Mathur, Andreas Pavlogiannis
Data races are among the most common bugs in concurrency. The standard approach to data-race detection is via dynamic analyses, which work over executions of concurrent programs, i…
Indivisible Mixed Manna: On the Computability of MMS + PO Allocations
Rucha Kulkarni, Ruta Mehta, Setareh Taki
In this paper we initiate the study of finding fair and efficient allocations of an indivisible mixed manna: Divide m indivisible items among n agents under the fairness notion of…
Approximating Nash Social Welfare under Submodular Valuations through (Un)Matchings
Jugal Garg, Pooja Kulkarni, Rucha Kulkarni
We study the problem of approximating maximum Nash social welfare (NSW) when allocating m indivisible items among n asymmetric agents with submodular valuations. The NSW is a well-…
Smoothed Efficient Algorithms and Reductions for Network Coordination Games
Shant Boodaghians, Rucha Kulkarni, Ruta Mehta
Worst-case hardness results for most equilibrium computation problems have raised the need for beyond-worst-case analysis. To this end, we study the smoothed complexity of finding…