Vincent Cohen-Addad

Distributed Algorithms for Euclidean Clustering

Nearly Space-Optimal Graph and Hypergraph Sparsification in Insertion-Only Data Streams

Less is More: Adaptive Coverage Sampling for Synthetic Training Data

Universal Ordering for Efficient PAC Learning

Data Selection and Active Learning via Low-Rank Approximation

Correlation Clustering Beyond the Pivot Algorithm

Fair Clustering in the Sliding Window Model

Algorithms and Hardness for Active Learning on Graphs

Scalable Private Partition Selection via Adaptive Weighting

The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence

REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective

Efficient Data Selection at Scale via Influence Distillation