activity
20182025
most citedOn Finding Dense Common Subgraphs

12 citations · 13 across the 4 of their papers we have counts for

collaborators

5 papers

cs.DS2025

Graph-based Nearest Neighbors with Dynamic Updates via Random Walks

Nina Mishra, Yonatan Naamad, Tal Wagner +1

Approximate nearest neighbor search (ANN) is a common way to retrieve relevant search results, especially now in the context of large language models and retrieval augmented genera…

cs.DS2023

Fast Private Kernel Density Estimation via Locality Sensitive Quantization

Tal Wagner, Yonatan Naamad, Nina Mishra

We study efficient mechanisms for differentially private kernel density estimation (DP-KDE). Prior work for the Gaussian kernel described algorithms that run in time exponential in…

cs.LG2023★ 1 cited

Explaining a machine learning decision to physicians via counterfactuals

Supriya Nagesh, Nina Mishra, Yonatan Naamad +3

Machine learning models perform well on several healthcare tasks and can help reduce the burden on the healthcare system. However, the lack of explainability is a major roadblock t…

cs.DS2018

Multi-Commodity Flow with In-Network Processing

Moses Charikar, Yonatan Naamad, Jennifer Rexford +1

Modern networks run "middleboxes" that offer services ranging from network address translation and server load balancing to firewalls, encryption, and compression. In an industry t…

cs.DS2018★ 12 cited

On Finding Dense Common Subgraphs

Moses Charikar, Yonatan Naamad, Jimmy Wu

We study the recently introduced problem of finding dense common subgraphs: Given a sequence of graphs that share the same vertex set, the goal is to find a subset of vertices …