6 citations · 26 across the 22 of their papers we have counts for
7 papers · 1 filter
Towards Automating Scientific Review with Google's Paper Assistant Tool
Rajesh Jayaram, Drew Tyler, David Woodruff +4
Artificial intelligence is driving a revolution in scientific discovery, accelerating everything from hypothesis generation to mathematical theorem proving. However, this rapid acc…
Private Training & Data Generation by Clustering Embeddings
Felix Zhou, Samson Zhou, Vahab Mirrokni +2
Deep neural networks often use large, high-quality datasets to achieve high performance on many machine learning tasks. When training involves potentially sensitive data, this proc…
Multi-View Stochastic Block Models
Vincent Cohen-Addad, Tommaso d'Orsi, Silvio Lattanzi +1
Graph clustering is a central topic in unsupervised learning with a multitude of practical applications. In recent years, multi-view graph clustering has gained a lot of attention…
Perturb-and-Project: Differentially Private Similarities and Marginals
Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto +2
We revisit the input perturbations framework for differential privacy where noise is added to the input and the result is then projected back to the space of adm…
Differentially-Private Hierarchical Clustering with Provable Approximation Guarantees
Jacob Imola, Alessandro Epasto, Mohammad Mahdian +2
Hierarchical Clustering is a popular unsupervised machine learning method with decades of history and numerous applications. We initiate the study of differentially private approxi…
Near-Optimal Correlation Clustering with Privacy
Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi +4
Correlation clustering is a central problem in unsupervised learning, with applications spanning community detection, duplicate detection, automated labelling and many more. In the…