Sergei Vassilvitskii
29 papers · 2013–2026 · 8 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (50) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π¬
Deep Specialist
(10)
π
Keyword Champion
(2)
π§
Keyword Pioneer
π
Conference Pioneer
β‘
Prolific Year Β· Productive
ποΈ
Keyword Collector
(130)
π₯
Unstoppable Β· Silver
π
Renaissance Researcher
(7)
π
Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(27)
Optimization & Theory
(17)
Mathematics & Optimization
(14)
Optimization
(11)
Core Methods
(10)
Application Areas
(9)
Artificial Intelligence
(7)
Learning Types
(6)
Core AI
(5)
Computer Science
(4)
Natural Language Processing
(4)
Security & Privacy
(4)
Differential Privacy
(4)
Foundations
(4)
Data Science & Analytics
(3)
Keywords
differential privacy
(8)
online algorithm
(5)
sample complexity
(3)
competitive analysis
(3)
model memorization
(2)
synthetic data
(2)
machine-learned prediction
(2)
online learning
(2)
label privacy
(2)
fair clustering
(2)
warm starting
(2)
text-to-text transformer
(2)
approximation algorithm
(2)
graph algorithm
(2)
privacy-preserving training
(2)
online clustering
(1)
matrix factorization
(1)
learning theory
(1)
game theory
(1)
transfer learning
(1)
Papers
Learning from Synthetic Data: Limitations of ERM
ALT 2026
Scaling Laws for Downstream Task Performance in Machine Translation
ICLR 2025
Binary Search with Distributional Predictions
NeurIPS 2024
Private prediction for large-scale synthetic text generation
EMNLP 2024
Warm-starting Push-Relabel
NeurIPS 2024
Easy Differentially Private Linear Regression
ICLR 2023
Label differential privacy and private training data release
ICML 2023
Learning-augmented private algorithms for multiple quantile release
ICML 2023
Predictive Flows for Faster Ford-Fulkerson
ICML 2023
Speeding Up Bellman Ford via Minimum Violation Permutations
ICML 2023
Algorithms with Prediction Portfolios
NeurIPS 2022
Label differential privacy via clustering
AISTATS 2022
Learning Predictions for Algorithms with Predictions
NeurIPS 2022
Training Text-to-Text Transformers with Privacy Guarantees
ACL 2022
Training Text-to-Text Transformers with Privacy Guarantees
NAACL 2022
Faster Matchings via Learned Duals
NeurIPS 2021
Robust Online Correlation Clustering
NeurIPS 2021
Fair Hierarchical Clustering
NeurIPS 2020
Sliding Window Algorithms for k-Clustering Problems
NeurIPS 2020
Differentially Private Covariance Estimation
NeurIPS 2019
Maximizing Induced Cardinality Under a Determinantal Point Process
NeurIPS 2018
Consistent k-Clustering
ICML 2017
Fair Clustering Through Fairlets
NeurIPS 2017
Revenue Optimization with Approximate Bid Predictions
NeurIPS 2017
Statistical Cost Sharing
NeurIPS 2017
On Mixtures of Markov Chains
NeurIPS 2016
Pricing a Low-regret Seller
ICML 2016
Sketching, Embedding and Dimensionality Reduction in Information Theoretic Spaces
AISTATS 2016
Near-Optimal Bounds for Cross-Validation via Loss Stability
ICML 2013