Vincent Cohen-Addad
38 papers · 2017–2025 · 6 conferences · across top CS/AI conferences
Achievements
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๐ Academic Marathon (8) ๐ Interdisciplinary Bridge ๐งญ Keyword Pioneer ๐ Conference Polyglot (6) ๐ Cross-Pollinator (10)
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Cross-Pollinator
(10)
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Renaissance Researcher
(8)
๐บ๏ธ
Taxonomy Completionist
(29)
๐ฌ
Deep Specialist
(17)
๐ค
Dynamic Duo
(11)
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Keyword Champion
(4)
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Century Club
(38)
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Trend Setter
๐ฅ
Unstoppable
(9)
โก
Prolific Year
(8)
๐๏ธ
Keyword Collector
(93)
Conferences
ICML (16)
NIPS (14)
AISTATS (4)
COLT (2)
EMNLP (1)
ICLR (1)
Top co-authors
Research topics
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 RedemptionโBeyond the Impossibility of Kleinbergโs Axioms
NIPS 2018
Hierarchical Clustering Beyond the Worst-Case
NIPS 2017
Online Optimization of Smoothed Piecewise Constant Functions
AISTATS 2017