Vignesh Viswanathan
I am a Computer Science PhD candidate at the University of Massachusetts, Amherst working primarily with Prof. Yair Zick. Prior to joining UMass Amherst, I received my undergraduate degree at IIT Kharagpur.
I like working on combinatorial problems in computational economics. My current focus is on problems in fair allocation and two sided matching. I have also worked on graph arrangements, market equilibria and explainable AI during my PhD.
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Publications
Representative papers are highlighted.


Tight Approximations for Graphical House Allocation
Hadi Hosseini,
Andrew McGregor,
Rik Sengupta,
Rohit Vaish,
Vignesh Viswanathan
AAMAS, 2024
arXiv
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bibtex
Approximation algorithms for the graphical house allocation problem studied in our AAMAS 2023 paper. Also, Ramanujan graphs and a cool connection between graph cuts and bitstrings.


Axiomatic Aggregations of Abductive Explanations
Gagan Biradar,
Yacine Izza,
Elita Lobo,
Vignesh Viswanathan
Yair Zick
AAAI, 2024
arXiv
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bibtex
Cooperative game theory meets formal logic meets model explanations!


The Good, the Bad and the Submodular: Fairly Allocating Mixed Manna Under OrderNeutral Submodular Preferences
Cyrus Cousins
Vignesh Viswanathan,
Yair Zick
WINE, 2023
arXiv
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bibtex
Fair allocation of indivisible items when agents valuations are submodular and each item has a marginal contribution of 1, 0 or some positive integer c.


Dividing Good and Great Items Among Agents with Bivalued Submodular Valuations
Cyrus Cousins
Vignesh Viswanathan,
Yair Zick
WINE, 2023
arXiv
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bibtex
Algorithms for fair allocation of indivisible items when agents valuations are submodular and each item has a marginal contribution of 1 or some positive integer c.


A General Framework For Fair Allocation with Matroid Rank Valuations
Vignesh Viswanathan,
Yair Zick
EC, 2023
arXiv
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bibtex
A framework that implies efficient algorithms for almost all fairness objectives when agents have binary submodular valuations.


Yankee Swap: A Fast and Simple Fair Allocation Mechanism for Matroid Rank Valuations
Vignesh Viswanathan,
Yair Zick
AAMAS, 2023
arXiv
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bibtex
A fast algorithm for leximin allocations when agents have binary submodular valuations.


Graphical House Allocation
Hadi Hosseini,
Justin Payan,
Rik Sengupta,
Rohit Vaish,
Vignesh Viswanathan
AAMAS, 2023
arXiv
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bibtex
How to assign a set of numbers to the vertices of a graph so as to minimize the sum of absolute differences along the edges?


Relaxations of EnvyFreeness Over Graphs
Justin Payan,
Rik Sengupta,
Vignesh Viswanathan
AAMAS, 2023 (Extended Abstract)
arXiv
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bibtex
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Code
Can we compute allocations that satisfy the envyfree up to any good (EFX) condition only for certain pairs of agents?


Moving Target Defense under Uncertainty for Web Applications
Vignesh Viswanathan,
Megha Bose,
Praveen Paruchuri
AAMAS, 2022 (Extended Abstract)
arXiv
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bibtex
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Code
Can we hide the vulnerabilities of a web application by randomizing over multiple implementations?


The Price is (Probably) Right: Learning Market Equilibria From Samples
Neel Patel,
Omer Lev,
Vignesh Viswanathan,
Yair Zick
AAMAS, 2021
arXiv
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bibtex
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Code
Algorithms to compute approximate market equilibria when the only knowledge of agent preferences comes from samples.


Fighting Wildfires under Uncertainty: A Sequential Resource Allocation Approach
Hau Chan,
Long TranThanh,
Vignesh Viswanathan
IJCAI, 2020
Paper
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bibtex
Allocating scarce firefighting resources to different regions under uncertainty.

Other Ramblings
Shorter notes with smaller results.


Weighted Notions of Fairness with Binary Supermodular Chores
Vignesh Viswanathan,
Yair Zick
arXiv, 2023
arXiv
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bibtex
We can build a general Yankee Swap type framework for binary chores as well!

