7 citations · 8 across the 10 of their papers we have counts for
10 papers
Compact Representations of Geometric Bipartite Graphs via Weighted Biclique Covers
Aryan Esmailpour, Khoi Le, Stavros Sintos
Bipartite graphs are a fundamental representation for relational data arising in recommendation systems, social networks, and communication graphs. A key challenge in these setting…
Faster Relational Algorithms Using Geometric Data Structures
Aryan Esmailpour, Stavros Sintos
Optimization tasks over relational data, such as clustering, often suffer from the prohibitive cost of join operations, which are necessary to access the full dataset. While geomet…
Metric -clustering using only Weak Comparison Oracles
Rahul Raychaudhury, Aryan Esmailpour, Sainyam Galhotra +1
Clustering is a fundamental primitive in unsupervised learning. However, classical algorithms for -clustering (such as -median and -means) assume access to exact pairwise…
Dynamic Necklace Splitting
Rishi Advani, Abolfazl Asudeh, Mohsen Dehghankar +1
The necklace splitting problem is a classic problem in fair division with many applications, including data-informed fair hash maps. We extend necklace splitting to a dynamic setti…
On Fair Epsilon Net and Geometric Hitting Set
Mohsen Dehghankar, Stavros Sintos, Abolfazl Asudeh
Fairness has emerged as a formidable challenge in data-driven decisions. Many of the data problems, such as creating compact data summaries for approximate query processing, can be…
Fair-Count-Min: Frequency Estimation under Equal Group-wise Approximation Factor
Nima Shahbazi, Stavros Sintos, Abolfazl Asudeh
Frequency estimation in streaming data often relies on sketches like Count-Min (CM) to provide approximate answers with sublinear space. However, CM sketches introduce additive err…
A Theoretical Framework for Distribution-Aware Dataset Search
Aryan Esmailpour, Sainyam Galhotra, Rahul Raychaudhury +1
Effective data discovery is a cornerstone of modern data-driven decision-making. Yet, identifying datasets with specific distributional characteristics, such as percentiles or pref…
Improved Approximation Algorithms for Relational Clustering
Aryan Esmailpour, Stavros Sintos
Clustering plays a crucial role in computer science, facilitating data analysis and problem-solving across numerous fields. By partitioning large datasets into meaningful groups, c…
Faster Algorithms for Fair Max-Min Diversification in
Yash Kurkure, Miles Shamo, Joseph Wiseman +2
The task of extracting a diverse subset from a dataset, often referred to as maximum diversification, plays a pivotal role in various real-world applications that have far-reaching…
A Fair and Memory/Time-efficient Hashmap
Abolfazl Asudeh, Nima Shahbazi, Stavros Sintos
Hashmap is a fundamental data structure in computer science. There has been extensive research on constructing hashmaps that minimize the number of collisions leading to efficient…