activity
20132020
most citedBeating Greedy for Stochastic Bipartite Matching

16 citations · 18 across the 3 of their papers we have counts for

collaborators

7 papers

cs.DS2020

Robust Algorithms under Adversarial Injections

Paritosh Garg, Sagar Kale, Lars Rohwedder +1

In this paper, we study streaming and online algorithms in the context of randomness in the input. For several problems, a random order of the input sequence---as opposed to the wo…

cs.DS2020

Fully-Dynamic Coresets

Monika Henzinger, Sagar Kale

With input sizes becoming massive, coresets -- small yet representative summary of the input -- are relevant more than ever. A weighted set that is a subset of the input is a…

cs.DS20202 cited

How to Solve Fair -Center in Massive Data Models

Ashish Chiplunkar, Sagar Kale, Sivaramakrishnan Natarajan Ramamoorthy

Fueled by massive data, important decision making is being automated with the help of algorithms, therefore, fairness in algorithms has become an especially important research topi…

cs.DS201916 cited

Beating Greedy for Stochastic Bipartite Matching

Buddhima Gamlath, Sagar Kale, Ola Svensson

We consider the maximum bipartite matching problem in stochastic settings, namely the query-commit and price-of-information models. In the query-commit model, an edge e independent…

cs.DS2018

Weighted Matchings via Unweighted Augmentations

Buddhima Gamlath, Sagar Kale, Slobodan Mitrović +1

We design a generic method for reducing the task of finding weighted matchings to that of finding short augmenting paths in unweighted graphs. This method enables us to provide eff…

cs.DS2018

Small Space Stream Summary for Matroid Center

Sagar Kale

In the matroid center problem, which generalizes the -center problem, we need to pick a set of centers that is an independent set of a matroid with rank . We study this probl…