Vishwa Prakash HV

dblp:279/6491 · DBLP profile ↗
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7ranked-venue papers
2as first author
7since 2021 · last 2026
0009-0002-4809-5814ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4 · 2 first-author · 4 since 2021Graphics, computer vision, multimedia, augmented reality and games · 3 · 1 first-author · 3 since 2021Theory of computation · 2 · 1 first-author · 2 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
YearPublicationVenuePosition
2026 Best of Both Worlds Guarantees for Equitable Allocations
Umang Bhaskar, Vishwa Prakash HV, Aditi Sethia, Rakshitha
AAAI2
2025 (Almost Full) EFX for Three (and More) Types of Agents
abstract
We study the problem of determining an envy-free allocation of indivisible goods among multiple agents with additive valuations. EFX, which stands for envy-freeness up to any good, is a well-studied relaxation of the envy-free allocation problem and has been shown to exist for specific scenarios. EFX is known to exist for three agents, and for any number of agents when there are only two types of valuations. EFX allocations are also known to exist for four agents with at most one good unallocated. In this paper, we show that EFX exists with at most k-2 goods unallocated for any number of agents having k distinct valuations. Additionally, we show that complete EFX allocations exist when all but two agents have identical valuations.
Pratik Ghosal, Vishwa Prakash HV, Prajakta Nimbhorkar, Nithin Varma 0001
AAAI2
2025 Fair and Efficient Completion of Indivisible Goods
abstract
We formulate the problem of fair and efficient completion of indivisible goods, defined as follows: Given a partial allocation of indivisible goods among agents, does there exist an allocation of the remaining goods (i.e., a completion) that satisfies fairness and economic efficiency guarantees of interest? We study the computational complexity of the completion problem for prominent fairness and efficiency notions such as envy-freeness up to one good (EF1), proportionality up to one good (Prop1), maximin share (MMS), and Pareto optimality (PO), and focus on the class of additive valuations as well as its subclasses such as binary additive and lexicographic valuations. We find that while the completion problem is significantly harder than the standard fair division problem (wherein the initial partial allocation is empty), the consideration of restricted preferences facilitates positive algorithmic results for threshold-based fairness notions (Prop1 and MMS). On the other hand, the completion problem remains computationally intractable for envy-based notions such as EF1 and EF1+PO even under restricted preferences.
Vishwa Prakash HV, Ayumi Igarashi 0001, Rohit Vaish
AAAI1
2025 EFX Exists for Three Types of Agents
abstract
We study the problem of finding an envy-free allocation of indivisible goods among agents with additive valuations. We focus on the fairness notion of envy-freeness up to any good (EFX). A central open question in fair division is whether EFX allocations always exist for any number of agents. While EFX has been established for three agents [Chaudhury et al., 2024] and for any number of agents with at most two distinct valuations [Mahara, 2023], its existence in more general settings remains open.
Vishwa Prakash HV, Pratik Ghosal, Prajakta Nimbhorkar, Nithin Varma 0001
EC1
2025 Fair and Efficient Allocation of Indivisible Mixed Manna
Siddharth Barman, Vishwa Prakash HV, Aditi Sethia, Mashbat Suzuki
WINE2
2023 Fair Healthcare Rationing to Maximize Dynamic Utilities
Aadityan Ganesh, Pratik Ghosal, Vishwa Prakash HV, Prajakta Nimbhorkar
PAKDD (2)3
2021 Disjoint Stable Matchings in Linear Time
Aadityan Ganesh, Vishwa Prakash HV, Prajakta Nimbhorkar, Geevarghese Philip
WG2