3 citations · 4 across the 11 of their papers we have counts for
13 papers
Packing Compact Subgraphs with Applications to Districting
Ho-Lin Chen, Po-Yu Chou, Prathamesh Dharangutte +3
Packing disjoint subgraphs in a given graph is a fundamental problem with many applications. Motivated by political districting, we focus on connected subgraphs that are compact (e…
The Price of Privacy For Approximating Max-CSP
Prathamesh Dharangutte, Jingcheng Liu, Pasin Manurangsi +3
We study approximation algorithms for Maximum Constraint Satisfaction Problems (Max-CSPs) under differential privacy (DP) where the constraints are considered sensitive data. Infor…
Relative Error Fair Clustering in the Weak-Strong Oracle Model
Vladimir Braverman, Prathamesh Dharangutte, Shaofeng H. -C. Jiang +4
We study fair clustering problems in a setting where distance information is obtained from two sources: a strong oracle providing exact distances, but at a high cost, and a weak or…
Hardness and Approximation Algorithms for Balanced Districting Problems
Prathamesh Dharangutte, Jie Gao, Shang-En Huang +1
We introduce and study the problem of balanced districting, where given an undirected graph with vertices carrying two types of weights (different population, resource types, etc)…
Fully Dynamic Adversarially Robust Correlation Clustering in Polylogarithmic Update Time
Vladimir Braverman, Prathamesh Dharangutte, Shreyas Pai +2
We study the dynamic correlation clustering problem with edge label flips. In correlation clustering, we are given a -vertex complete graph whose edges are l…
Learning-augmented Maximum Independent Set
Vladimir Braverman, Prathamesh Dharangutte, Vihan Shah +1
We study the Maximum Independent Set (MIS) problem on general graphs within the framework of learning-augmented algorithms. The MIS problem is known to be NP-hard and is also NP-ha…
Differentially Private Range Queries with Correlated Input Perturbation
Prathamesh Dharangutte, Jie Gao, Ruobin Gong +1
This work proposes a class of differentially private mechanisms for linear queries, in particular range queries, that leverages correlated input perturbation to simultaneously achi…
Metric Clustering and MST with Strong and Weak Distance Oracles
MohammadHossein Bateni, Prathamesh Dharangutte, Rajesh Jayaram +1
We study optimization problems in a metric space where we can compute distances in two ways: via a ''strong'' oracle that returns exact distances , and a…
Integer Subspace Differential Privacy
Prathamesh Dharangutte, Jie Gao, Ruobin Gong +1
We propose new differential privacy solutions for when external \emph{invariants} and \emph{integer} constraints are simultaneously enforced on the data product. These requirements…
A Tight Analysis of Hutchinson's Diagonal Estimator
Prathamesh Dharangutte, Christopher Musco
Let be a matrix with diagonal and let be with its diagonal set to all zeros. We sho…
Dynamic Trace Estimation
Prathamesh Dharangutte, Christopher Musco
We study a dynamic version of the implicit trace estimation problem. Given access to an oracle for computing matrix-vector multiplications with a dynamically changing matrix A, our…
An Energy-Based View of Graph Neural Networks
John Y. Shin, Prathamesh Dharangutte
Graph neural networks are a popular variant of neural networks that work with graph-structured data. In this work, we consider combining graph neural networks with the energy-based…
Graph Learning for Inverse Landscape Genetics
Prathamesh Dharangutte, Christopher Musco
The problem of inferring unknown graph edges from numerical data at a graph's nodes appears in many forms across machine learning. We study a version of this problem that arises in…