5 papers
Active Learning with Low-Rank Structure for Data Selection
Vincent Cohen-Addad, Sasidhar Kunapuli, Vahab Mirrokni +3
In the data selection problem, the objective is to choose a small, representative subset of data that can be used to efficiently train a machine learning model. Sener and Savarese…
An Efficient Private Algorithm for Community Detection
Vincent Cohen-Addad, Alessandro Epasto, Haim Kaplan +2
In this paper, we study the community detection problem in the stochastic block model (SBM) under privacy constraints. We introduce private and highly efficient algorithms for exac…
Distributed Algorithms for Euclidean Clustering
Vincent Cohen-Addad, Liudeng Wang, David P. Woodruff +1
We study the problem of constructing -coresets for Euclidean -clustering in the distributed setting, where data points are partitioned across sites.…
Nearly Space-Optimal Graph and Hypergraph Sparsification in Insertion-Only Data Streams
Vincent Cohen-Addad, David P. Woodruff, Shenghao Xie +1
We study the problem of graph and hypergraph sparsification in insertion-only data streams. The input is a hypergraph with nodes, hyperedges, and rank , an…
Fast, Space-Optimal Streaming Algorithms for Clustering and Subspace Embeddings
Vincent Cohen-Addad, Liudeng Wang, David P. Woodruff +1
We show that both clustering and subspace embeddings can be performed in the streaming model with the same asymptotic efficiency as in the central/offline setting. For -clu…