← Authors

Vincent Cohen-Addad

38 papers · 2017–2025 · 6 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) πŸƒ Academic Marathon (8) 🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (29) πŸ”¬ Deep Specialist (17) 🀝 Dynamic Duo (11) πŸ† Keyword Champion (4) πŸ’Ž Century Club (38) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (9) ⚑ Prolific Year (8) πŸ—ƒοΈ Keyword Collector (93)

Conferences

ICML (16) NIPS (14) AISTATS (4) COLT (2) EMNLP (1) ICLR (1)

Top co-authors

Silvio Lattanzi (11) David Saulpic (6) Nikos Parotsidis (6) Alessandro Epasto (6) Vahab Mirrokni (5) Varun Kanade (4) Tommaso d’Orsi (4) Frederik Mallmann-Trenn (4) Ashkan Norouzi-Fard (4) Chris Schwiegelshohn (3)

Research topics

Differential Privacy (2)

Keywords

approximation algorithm (12) stochastic block model (5) hierarchical clustering (5) clustering algorithm (5) k-means clustering (5) euclidean space (4) differential privacy (4) massively parallel computation (3) graph clustering (3) unsupervised learning (3) correlation clustering (3) single linkage (2) community detection (2) regret bound (2) k-median clustering (2) algorithm design (2) local search (2) nearest neighbor (1) online learning (1) network analysis (1)

Papers

The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence ICML 2025
Metric Embeddings Beyond Bi-Lipschitz Distortion via Sherali-Adams COLT 2025
Fair Clustering in the Sliding Window Model ICLR 2025
Correlation Clustering Beyond the Pivot Algorithm ICML 2025
Scalable Private Partition Selection via Adaptive Weighting ICML 2025
Algorithms and Hardness for Active Learning on Graphs ICML 2025
REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective ICML 2025
Re-Invoke: Tool Invocation Rewriting for Zero-Shot Tool Retrieval EMNLP 2024
Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond ICML 2024
A Scalable Algorithm for Individually Fair k-Means Clustering AISTATS 2024
Multi-View Stochastic Block Models ICML 2024
Perturb-and-Project: Differentially Private Similarities and Marginals ICML 2024
Dynamic Correlation Clustering in Sublinear Update Time ICML 2024
Learning-Augmented Approximation Algorithms for Maximum Cut and Related Problems NIPS 2024
A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering ICML 2024
Private estimation algorithms for stochastic block models and mixture models NIPS 2023
Multi-Swap k-Means++ NIPS 2023
Differentially Private Hierarchical Clustering with Provable Approximation Guarantees ICML 2023
Near-Optimal Correlation Clustering with Privacy NIPS 2022
Massively Parallel $k$-Means Clustering for Perturbation Resilient Instances ICML 2022
Improved Coresets for Euclidean $k$-Means NIPS 2022
On Facility Location Problem in the Local Differential Privacy Model AISTATS 2022
Community Recovery in the Degree-Heterogeneous Stochastic Block Model COLT 2022
Near-Optimal Private and Scalable $k$-Clustering NIPS 2022
Online and Consistent Correlation Clustering ICML 2022
Improved Coresets and Sublinear Algorithms for Power Means in Euclidean Spaces NIPS 2021
Online k-means Clustering AISTATS 2021
Improving Ultrametrics Embeddings Through Coresets ICML 2021
Correlation Clustering in Constant Many Parallel Rounds ICML 2021
Parallel and Efficient Hierarchical k-Median Clustering NIPS 2021
On Efficient Low Distortion Ultrametric Embedding ICML 2020
On the Power of Louvain in the Stochastic Block Model NIPS 2020
Fast and Accurate $k$-means++ via Rejection Sampling NIPS 2020
Fully Dynamic Consistent Facility Location NIPS 2019
Subquadratic High-Dimensional Hierarchical Clustering NIPS 2019
Clustering Redemption–Beyond the Impossibility of Kleinberg’s Axioms NIPS 2018
Hierarchical Clustering Beyond the Worst-Case NIPS 2017
Online Optimization of Smoothed Piecewise Constant Functions AISTATS 2017