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Pankaj K Agarwal

7 accepted papers

2026

A Scalable Constant-Factor Approximation Algorithm for $W_p$ Optimal Transport

ICLR 2026poster

Let $(X,d)$ be a metric space and let $\mu,\nu$ be discrete distributions supported on finite point sets $A,B \subseteq X$. For any $p \in [1,\infty]$, the $W_p$-distance between $\mu$ and $\nu$, $W_p(\mu, \nu)$, is defined as the $p$-th root of the minimum cost of transporting the mass from $\mu$ t…

Cited by 0SourceScholar
2025

De-coupled NeuroGF for Shortest Path Distance Approximations on Large Terrain Graphs

ICML 2025poster

The ability to acquire high-resolution, large-scale geospatial data at an unprecedented using LiDAR and other related technologies has intensified the need for scalable algorithms for terrain analysis, including *shortest-path-distance* (SPD) queries on large-scale terrain digital elevation models (…

Cited by 0SourcePDFScholar
2025

Efficient Algorithms for Robust and Partial Semi-Discrete Optimal Transport

NeurIPS 2025poster

The sensitivity of optimal transport (OT) to noise has motivated the study of robust variants. In this paper, we study two such formulations of semi-discrete OT in $\mathbb{R}^d$: (i) the $\alpha$-optimal partial transport, which minimizes the cost of transporting a mass of $\alpha$; and (ii) the $\…

Cited by 0SourceScholar
2024

A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem

NeurIPS 2024poster

Optimal Transport (OT, also known as the Wasserstein distance) is a popular metric for comparing probability distributions and has been successfully used in many machine-learning applications. In the semi-discrete $2$-Wasserstein problem, we wish to compute the cheapest way to transport all the mass…

Cited by 1SourcePDFScholar
2023

A Higher Precision Algorithm for Computing the $1$-Wasserstein Distance

ICLR 2023top-25%

We consider the problem of computing the $1$-Wasserstein distance $\mathcal{W}(\mu,\nu)$ between two $d$-dimensional discrete distributions $\mu$ and $\nu$ whose support lie within the unit hypercube. There are several algorithms that estimate $\mathcal{W}(\mu,\nu)$ within an additive error of $\var…

Cited by 6SourcePDFScholar
2022

All Politics is Local: Redistricting via Local Fairness

NeurIPS 2022accept

In this paper, we propose to use the concept of local fairness for auditing and ranking redistricting plans. Given a redistricting plan, a deviating group is a population-balanced contiguous region in which a majority of individuals are of the same interest and in the minority of their respective di…

Cited by 8SourcePDFScholar