Sergei Vassilvitskii

188 papers A* 60A 20B 7C 1Misc 1Journal 77Unranked 20

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AI-rithmetic. CoRR Alex Bie, Travis Dick, Alex Kulesza, Prabhakar Raghavan, Vinod Raman, Sergei Vassilvitskii
2026	J	`jnl`	Learning from Synthetic Data: Limitations of ERM. CoRR Kareem Amin, Alex Bie, Weiwei Kong, Umar Syed, Sergei Vassilvitskii
2025	A*	`conf`	Almost Tight Bounds for Differentially Private Densest Subgraph. SODA Michael Dinitz, Satyen Kale, Silvio Lattanzi, Sergei Vassilvitskii
2025	J	`jnl`	An Optimization Framework for Differentially Private Sparse Fine-Tuning. CoRR Mehdi Makni, Kayhan Behdin, Gabriel Afriat, Zheng Xu, Sergei Vassilvitskii, Natalia Ponomareva, Hussein Hazimeh, Rahul Mazumder
2025	A	`conf`	Data-Driven Solution Portfolios. ITCS Marina Drygala, Silvio Lattanzi, Andreas Maggiori, Miltiadis Stouras, Ola Svensson, Sergei Vassilvitskii
2025	—	`conf`	Differentially Private Synthetic Data Release for Topics API Outputs. KDD (2) Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Andrés Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong
2025	J	`jnl`	Differentially Private Synthetic Data Release for Topics API Outputs. CoRR Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Andrés Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong
2025	J	`jnl`	Escaping Collapse: The Strength of Weak Data for Large Language Model Training. CoRR Kareem Amin, Sara Babakniya, Alex Bie, Weiwei Kong, Umar Syed, Sergei Vassilvitskii
2025	J	`jnl`	How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy. CoRR Natalia Ponomareva, Zheng Xu, H. Brendan McMahan, Peter Kairouz, Lucas Rosenblatt, Vincent Cohen-Addad, Cristóbal Guzmán, Ryan McKenna, Galen Andrew, Alex Bie, Da Yu, Alex Kurakin, Morteza Zadimoghaddam, Sergei Vassilvitskii, Andreas Terzis
2025	J	`jnl`	Learned Predictions for Data Structures and Running Time (Dagstuhl Seminar 25181). Dagstuhl Reports Inge Li Gørtz, Benjamin Moseley, Shikha Singh, Sergei Vassilvitskii
2025	—	`conf`	SPARTA: An Optimization Framework for Differentially Private Sparse Fine-Tuning. KDD (2) Mehdi Makni, Kayhan Behdin, Gabriel Afriat, Zheng Xu, Sergei Vassilvitskii, Natalia Ponomareva, Rahul Mazumder, Hussein Hazimeh
2025	A*	`conf`	Scaling Laws for Downstream Task Performance in Machine Translation. ICLR Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo
2024	A*	`conf`	Binary Search with Distributional Predictions. NeurIPS Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Aidin Niaparast, Sergei Vassilvitskii
2024	J	`jnl`	Binary Search with Distributional Predictions. CoRR Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Aidin Niaparast, Sergei Vassilvitskii
2024	A*	`conf`	Controlling Tail Risk in Online Ski-Rental. SODA Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii
2024	J	`jnl`	Data-Driven Solution Portfolios. CoRR Marina Drygala, Silvio Lattanzi, Andreas Maggiori, Miltiadis Stouras, Ola Svensson, Sergei Vassilvitskii
2024	J	`jnl`	Practical Considerations for Differential Privacy. CoRR Kareem Amin, Alex Kulesza, Sergei Vassilvitskii
2024	—	`conf`	Private prediction for large-scale synthetic text generation. EMNLP (Findings) Kareem Amin, Alex Bie, Weiwei Kong, Alexey Kurakin, Natalia Ponomareva, Umar Syed, Andreas Terzis, Sergei Vassilvitskii
2024	J	`jnl`	Private prediction for large-scale synthetic text generation. CoRR Kareem Amin, Alex Bie, Weiwei Kong, Alexey Kurakin, Natalia Ponomareva, Umar Syed, Andreas Terzis, Sergei Vassilvitskii
2024	A	`ed.`	Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024 WSDM Luz Angelica Caudillo-Mata, Silvio Lattanzi, Andrés Muñoz Medina, Leman Akoglu, Aristides Gionis, Sergei Vassilvitskii
2024	J	`jnl`	Scaling Laws for Downstream Task Performance of Large Language Models. CoRR Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo
2024	J	`jnl`	Secretaries with Advice. Math. Oper. Res. Paul Dütting, Silvio Lattanzi, Renato Paes Leme, Sergei Vassilvitskii
2024	A*	`conf`	Warm-starting Push-Relabel. NeurIPS Sami Davies, Sergei Vassilvitskii, Yuyan Wang
2024	J	`jnl`	Warm-starting Push-Relabel. CoRR Sami Davies, Sergei Vassilvitskii, Yuyan Wang
2024	J	`jnl`	Winner-Pays-Bid Auctions Minimize Variance. CoRR R. Preston McAfee, Renato Paes Leme, Balasubramanian Sivan, Sergei Vassilvitskii
2023	J	`jnl`	Challenges towards the Next Frontier in Privacy. CoRR Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie J. Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang
2023	J	`jnl`	Controlling Tail Risk in Online Ski-Rental. CoRR Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii
2023	A	`conf`	Differentially Private Continual Releases of Streaming Frequency Moment Estimations. ITCS Alessandro Epasto, Jieming Mao, Andres Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong
2023	J	`jnl`	Differentially Private Continual Releases of Streaming Frequency Moment Estimations. CoRR Alessandro Epasto, Jieming Mao, Andres Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong
2023	A*	`conf`	Easy Differentially Private Linear Regression. ICLR Kareem Amin, Matthew Joseph, Mónica Ribero, Sergei Vassilvitskii
2023	J	`jnl`	How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy. CoRR Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin, Zheng Xu, Carson Denison, H. Brendan McMahan, Sergei Vassilvitskii, Steve Chien, Abhradeep Thakurta
2023	J	`jnl`	How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy. J. Artif. Intell. Res. Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin, Zheng Xu, Carson Denison, H. Brendan McMahan, Sergei Vassilvitskii, Steve Chien, Abhradeep Guha Thakurta
2023	A*	`conf`	How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy. KDD Natalia Ponomareva, Sergei Vassilvitskii, Zheng Xu, Brendan McMahan, Alexey Kurakin, Chiyaun Zhang
2023	J	`jnl`	Improved Differentially Private Densest Subgraph: Local and Purely Additive. CoRR Michael Dinitz, Satyen Kale, Silvio Lattanzi, Sergei Vassilvitskii
2023	A*	`conf`	Label differential privacy and private training data release. ICML Róbert Istvan Busa-Fekete, Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii
2023	A*	`conf`	Learning-augmented private algorithms for multiple quantile release. ICML Mikhail Khodak, Kareem Amin, Travis Dick, Sergei Vassilvitskii
2023	J	`jnl`	Massively Parallel Computation: Algorithms and Applications. Found. Trends Optim. Sungjin Im, Ravi Kumar, Silvio Lattanzi, Benjamin Moseley, Sergei Vassilvitskii
2023	J	`jnl`	Measuring Re-identification Risk. CoRR CJ Carey, Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Shankar Kumar, Andrés Muñoz Medina, Vahab Mirrokni, Gabriel Henrique Nunes, Sergei Vassilvitskii, Peilin Zhong
2023	J	`jnl`	Measuring Re-identification Risk. Proc. ACM Manag. Data CJ Carey, Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Shankar Kumar, Andres Muñoz Medina, Vahab Mirrokni, Gabriel Henrique Nunes, Sergei Vassilvitskii, Peilin Zhong
2023	A*	`conf`	Predictive Flows for Faster Ford-Fulkerson. ICML Sami Davies, Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang
2023	J	`jnl`	Predictive Flows for Faster Ford-Fulkerson. CoRR Sami Davies, Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang
2023	J	`jnl`	Scheduling (Dagstuhl Seminar 23061). Dagstuhl Reports Nicole Megow, Benjamin Moseley, David B. Shmoys, Ola Svensson, Sergei Vassilvitskii, Jens Schlöter
2023	A*	`conf`	Speeding Up Bellman Ford via Minimum Violation Permutations. ICML Silvio Lattanzi, Ola Svensson, Sergei Vassilvitskii
2022	A*	`conf`	Algorithms with Prediction Portfolios. NeurIPS Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii
2022	J	`jnl`	Algorithms with Prediction Portfolios. CoRR Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii
2022	J	`jnl`	Algorithms with predictions. Commun. ACM Michael Mitzenmacher, Sergei Vassilvitskii
2022	J	`jnl`	Easy Differentially Private Linear Regression. CoRR Kareem Amin, Matthew Joseph, Mónica Ribero, Sergei Vassilvitskii
2022	A	`conf`	Label differential privacy via clustering. AISTATS Hossein Esfandiari, Vahab S. Mirrokni, Umar Syed, Sergei Vassilvitskii
2022	A*	`conf`	Learning Predictions for Algorithms with Predictions. NeurIPS Misha Khodak, Maria-Florina Balcan, Ameet Talwalkar, Sergei Vassilvitskii
2022	J	`jnl`	Learning Predictions for Algorithms with Predictions. CoRR Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar, Sergei Vassilvitskii
2022	J	`jnl`	Plume: Differential Privacy at Scale. CoRR Kareem Amin, Jennifer Gillenwater, Matthew Joseph, Alex Kulesza, Sergei Vassilvitskii
2022	J	`jnl`	Private Algorithms with Private Predictions. CoRR Kareem Amin, Travis Dick, Mikhail Khodak, Sergei Vassilvitskii
2022	A*	`conf`	Scalable Differentially Private Clustering via Hierarchically Separated Trees. KDD Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab Mirrokni, Andres Muñoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii
2022	J	`jnl`	Scalable Differentially Private Clustering via Hierarchically Separated Trees. CoRR Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab S. Mirrokni, Andres Muñoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii
2022	J	`jnl`	Smooth Anonymity for Sparse Binary Matrices. CoRR Hossein Esfandiari, Alessandro Epasto, Vahab S. Mirrokni, Andres Muñoz Medina, Sergei Vassilvitskii
2022	—	`conf`	Training Text-to-Text Transformers with Privacy Guarantees. ACL (Findings) Natalia Ponomareva, Jasmijn Bastings, Sergei Vassilvitskii
2021	A*	`conf`	Clustering for Private Interest-based Advertising. KDD Alessandro Epasto, Andrés Muñoz Medina, Steven Avery, Yijian Bai, Róbert Busa-Fekete, CJ Carey, Ya Gao, David Guthrie, Subham Ghosh, James Ioannidis, Junyi Jiao, Jakub Lacki, Jason Lee, Arne Mauser, Brian Milch, Vahab S. Mirrokni, Deepak Ravichandran, Wei Shi, Max Spero, Yunting Sun, Umar Syed, Sergei Vassilvitskii, Shuo Wang
2021	J	`jnl`	Competitive Caching with Machine Learned Advice. J. ACM Thodoris Lykouris, Sergei Vassilvitskii
2021	A*	`conf`	Faster Matchings via Learned Duals. NeurIPS Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii
2021	J	`jnl`	Faster Matchings via Learned Duals. CoRR Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii
2021	A	`conf`	Hierarchical Clustering in General Metric Spaces using Approximate Nearest Neighbors. AISTATS Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang
2021	J	`jnl`	Label differential privacy via clustering. CoRR Hossein Esfandiari, Vahab S. Mirrokni, Umar Syed, Sergei Vassilvitskii
2021	A	`conf`	Private optimization without constraint violations. AISTATS Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii, Ellen Vitercik
2021	A*	`conf`	Robust Online Correlation Clustering. NeurIPS Silvio Lattanzi, Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang, Rudy Zhou
2021	A*	`conf`	Secretaries with Advice. EC Paul Dütting, Silvio Lattanzi, Renato Paes Leme, Sergei Vassilvitskii
2020	—	`ch.`	Algorithms with Predictions. Beyond the Worst-Case Analysis of Algorithms Michael Mitzenmacher, Sergei Vassilvitskii
2020	J	`jnl`	Algorithms with Predictions. CoRR Michael Mitzenmacher, Sergei Vassilvitskii
2020	A*	`conf`	Fair Hierarchical Clustering. NeurIPS Sara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar, Mohammad Mahdian, Benjamin Moseley, Philip Pham, Sergei Vassilvitskii, Yuyan Wang
2020	J	`jnl`	Fair Hierarchical Clustering. CoRR Sara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar, Mohammad Mahdian, Benjamin Moseley, Philip Pham, Sergei Vassilvitskii, Yuyan Wang
2020	A*	`conf`	Online Scheduling via Learned Weights. SODA Silvio Lattanzi, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii
2020	J	`jnl`	Private Optimization Without Constraint Violations. CoRR Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii, Ellen Vitercik
2020	Misc	`conf`	Residual Based Sampling for Online Low Rank Approximation. ITA Aditya Bhaskara, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
2020	J	`jnl`	Secretaries with Advice. CoRR Paul Dütting, Silvio Lattanzi, Renato Paes Leme, Sergei Vassilvitskii
2020	A*	`conf`	Sliding Window Algorithms for k-Clustering Problems. NeurIPS Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
2020	J	`jnl`	Sliding Window Algorithms for k-Clustering Problems. CoRR Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
2019	A*	`conf`	A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes. ICML Jennifer Gillenwater, Alex Kulesza, Zelda Mariet, Sergei Vassilvitskii
2019	A*	`conf`	Better Sliding Window Algorithms to Maximize Subadditive and Diversity Objectives. PODS Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
2019	A*	`conf`	Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy. ICML Kareem Amin, Alex Kulesza, Andres Muñoz Medina, Sergei Vassilvitskii
2019	A	`conf`	Consistent Online Optimization: Convex and Submodular. AISTATS Mohammad Reza Karimi Jaghargh, Andreas Krause, Silvio Lattanzi, Sergei Vassilvitskii
2019	A*	`conf`	Differentially Private Covariance Estimation. NeurIPS Kareem Amin, Travis Dick, Alex Kulesza, Andres Muñoz Medina, Sergei Vassilvitskii
2019	A	`conf`	Matroids, Matchings, and Fairness. AISTATS Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii
2019	A*	`conf`	Residual Based Sampling for Online Low Rank Approximation. FOCS Aditya Bhaskara, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
2018	A*	`conf`	Competitive Caching with Machine Learned Advice. ICML Thodoris Lykouris, Sergei Vassilvitskii
2018	J	`jnl`	Competitive caching with machine learned advice. CoRR Thodoris Lykouris, Sergei Vassilvitskii
2018	J	`jnl`	Fair Clustering Through Fairlets. CoRR Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii
2018	A*	`conf`	Maximizing Induced Cardinality Under a Determinantal Point Process. NeurIPS Jennifer A. Gillenwater, Alex Kulesza, Sergei Vassilvitskii, Zelda E. Mariet
2018	A	`conf`	Online Learning for Non-Stationary A/B Tests. CIKM Andrés Muñoz Medina, Sergei Vassilvitskii, Dong Yin
2018	J	`jnl`	Online Learning for Non-Stationary A/B Tests. CoRR Andrés Muñoz Medina, Sergei Vassilvitskii, Dong Yin
2018	J	`jnl`	Shuffles and Circuits (On Lower Bounds for Modern Parallel Computation). J. ACM Tim Roughgarden, Sergei Vassilvitskii, Joshua R. Wang
2018	A*	`conf`	Testing Incentive Compatibility in Display Ad Auctions. WWW Sébastien Lahaie, Andrés Muñoz Medina, Balasubramanian Sivan, Sergei Vassilvitskii
2017	A*	`conf`	Consistent k-Clustering. ICML Silvio Lattanzi, Sergei Vassilvitskii
2017	—	`conf`	Fair Clustering Through Fairlets. NIPS Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii
2017	A*	`conf`	Indexing Public-Private Graphs. WWW Aaron Archer, Silvio Lattanzi, Peter Likarish, Sergei Vassilvitskii
2017	J	`jnl`	Local Search Methods for k-Means with Outliers. Proc. VLDB Endow. Shalmoli Gupta, Ravi Kumar, Kefu Lu, Benjamin Moseley, Sergei Vassilvitskii
2017	—	`conf`	Revenue Optimization with Approximate Bid Predictions. NIPS Andres Muñoz Medina, Sergei Vassilvitskii
2017	J	`jnl`	Revenue Optimization with Approximate Bid Predictions. CoRR Andrés Muñoz Medina, Sergei Vassilvitskii
2017	—	`conf`	SQML: large-scale in-database machine learning with pure SQL. SoCC Umar Syed, Sergei Vassilvitskii
2017	—	`conf`	Statistical Cost Sharing. NIPS Eric Balkanski, Umar Syed, Sergei Vassilvitskii
2017	J	`jnl`	Statistical Cost Sharing. CoRR Eric Balkanski, Umar Syed, Sergei Vassilvitskii
2017	A*	`conf`	Submodular Optimization Over Sliding Windows. WWW Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
2016	A*	`conf`	A Field Guide to Personalized Reserve Prices. WWW Renato Paes Leme, Martin Pál, Sergei Vassilvitskii
2016	J	`jnl`	A Field Guide to Personalized Reserve Prices. CoRR Renato Paes Leme, Martin Pal, Sergei Vassilvitskii
2016	J	`jnl`	Incentivizing advertiser networks to submit multiple bids. Int. J. Game Theory Patrick Hummel, R. Preston McAfee, Sergei Vassilvitskii
2016	—	`conf`	On Mixtures of Markov Chains. NIPS Rishi Gupta, Ravi Kumar, Sergei Vassilvitskii
2016	A*	`conf`	Pricing a Low-regret Seller. ICML Hoda Heidari, Mohammad Mahdian, Umar Syed, Sergei Vassilvitskii, Sadra Yazdanbod
2016	B	`conf`	Shuffles and Circuits: (On Lower Bounds for Modern Parallel Computation). SPAA Tim Roughgarden, Sergei Vassilvitskii, Joshua R. Wang
2016	A	`conf`	Sketching, Embedding and Dimensionality Reduction in Information Theoretic Spaces. AISTATS Amirali Abdullah, Ravi Kumar, Andrew McGregor, Sergei Vassilvitskii, Suresh Venkatasubramanian
2016	J	`jnl`	Submodular Optimization over Sliding Windows. CoRR Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
2015	A*	`conf`	Algorithmic Cartography: Placing Points of Interest and Ads on Maps. KDD Mohammad Mahdian, Okke Schrijvers, Sergei Vassilvitskii
2015	J	`jnl`	Display Advertising Auctions with Arbitrage. ACM Trans. Economics and Comput. Ruggiero Cavallo, R. Preston McAfee, Sergei Vassilvitskii
2015	A	`conf`	Driven by Food: Modeling Geographic Choice. WSDM Ravi Kumar, Mohammad Mahdian, Bo Pang, Andrew Tomkins, Sergei Vassilvitskii
2015	J	`jnl`	Fast Greedy Algorithms in MapReduce and Streaming. ACM Trans. Parallel Comput. Ravi Kumar, Benjamin Moseley, Sergei Vassilvitskii, Andrea Vattani
2015	A	`conf`	Inverting a Steady-State. WSDM Ravi Kumar, Andrew Tomkins, Sergei Vassilvitskii, Erik Vee
2015	J	`jnl`	Sketching, Embedding, and Dimensionality Reduction for Information Spaces. CoRR Amirali Abdullah, Ravi Kumar, Andrew McGregor, Sergei Vassilvitskii, Suresh Venkatasubramanian
2015	J	`jnl`	To Match or Not to Match: Economics of Cookie Matching in Online Advertising. ACM Trans. Economics and Comput. Arpita Ghosh, Mohammad Mahdian, R. Preston McAfee, Sergei Vassilvitskii
2014	A*	`conf`	Advertising in a stream. WWW Samuel Ieong, Mohammad Mahdian, Sergei Vassilvitskii
2014	J	`jnl`	Algorithms for Large Scale Graphs (NII Shonan Meeting 2014-12). NII Shonan Meet. Rep. Andrew McGregor, Gopal Pandurangan, Sergei Vassilvitskii
2014	—	`conf`	Connected Components in MapReduce and Beyond. SoCC Raimondas Kiveris, Silvio Lattanzi, Vahab S. Mirrokni, Vibhor Rastogi, Sergei Vassilvitskii
2014	J	`jnl`	Parallel Algorithms for Unsupervised Tagging. Trans. Assoc. Comput. Linguistics Sujith Ravi, Sergei Vassilvitskii, Vibhor Rastogi
2014	A	`conf`	Scalable K-Means by ranked retrieval. WSDM Andrei Z. Broder, Lluis Garcia Pueyo, Vanja Josifovski, Sergei Vassilvitskii, Srihari Venkatesan
2014	A*	`conf`	The dynamics of repeat consumption. WWW Ashton Anderson, Ravi Kumar, Andrew Tomkins, Sergei Vassilvitskii
2014	B	`conf`	Value of Targeting. SAGT Kshipra Bhawalkar, Patrick Hummel, Sergei Vassilvitskii
2014	J	`jnl`	Value of Targeting. CoRR Kshipra Bhawalkar, Patrick Hummel, Sergei Vassilvitskii
2013	B	`conf`	Fast greedy algorithms in mapreduce and streaming. SPAA Ravi Kumar, Benjamin Moseley, Sergei Vassilvitskii, Andrea Vattani
2013	B	`conf`	MapReduce Algorithmics. WADS Sergei Vassilvitskii
2013	—	`conf`	Near-Optimal Bounds for Cross-Validation via Loss Stability. ICML (1) Ravi Kumar, Daniel Lokshtanov, Sergei Vassilvitskii, Andrea Vattani
2013	A	`conf`	Rank quantization. WSDM Ravi Kumar, Ronny Lempel, Roy Schwartz, Sergei Vassilvitskii
2013	A	`conf`	Sharding social networks. WSDM Quang Duong, Sharad Goel, Jake M. Hofman, Sergei Vassilvitskii
2012	B	`conf`	Ad Auctions with Data. SAGT Hu Fu, Patrick R. Jordan, Mohammad Mahdian, Uri Nadav, Inbal Talgam-Cohen, Sergei Vassilvitskii
2012	J	`jnl`	Ad Serving Using a Compact Allocation Plan CoRR Peiji Chen, Wenjing Ma, Srinath Mandalapu, Chandrashekhar Nagarajan, Jayavel Shanmugasundaram, Sergei Vassilvitskii, Erik Vee, Manfai Yu, Jason Y. Zien
2012	—	`conf`	Ad auctions with data. INFOCOM Workshops Hu Fu, Patrick R. Jordan, Mohammad Mahdian, Uri Nadav, Inbal Talgam-Cohen, Sergei Vassilvitskii
2012	A*	`conf`	Ad serving using a compact allocation plan. EC Peiji Chen, Wenjing Ma, Srinath Mandalapu, Chandrashekhar Nagarajan, Jayavel Shanmugasundaram, Sergei Vassilvitskii, Erik Vee, Manfai Yu, Jason Y. Zien
2012	J	`jnl`	Densest Subgraph in Streaming and MapReduce CoRR Bahman Bahmani, Ravi Kumar, Sergei Vassilvitskii
2012	J	`jnl`	Densest Subgraph in Streaming and MapReduce. Proc. VLDB Endow. Bahman Bahmani, Ravi Kumar, Sergei Vassilvitskii
2012	A*	`conf`	Handling forecast errors while bidding for display advertising. WWW Kevin J. Lang, Benjamin Moseley, Sergei Vassilvitskii
2012	C	`conf`	Inventory Allocation for Online Graphical Display Advertising using Multi-objective Optimization. ICORES Jian Yang, Erik Vee, Sergei Vassilvitskii, John A. Tomlin, Jayavel Shanmugasundaram, Tasos Anastasakos, Oliver Kennedy
2012	J	`jnl`	SHALE: An Efficient Algorithm for Allocation of Guaranteed Display Advertising CoRR Vijay Bharadwaj, Peiji Chen, Wenjing Ma, Chandrashekhar Nagarajan, John A. Tomlin, Sergei Vassilvitskii, Erik Vee, Jian Yang
2012	A*	`conf`	SHALE: an efficient algorithm for allocation of guaranteed display advertising. KDD Vijay Bharadwaj, Peiji Chen, Wenjing Ma, Chandrashekhar Nagarajan, John A. Tomlin, Sergei Vassilvitskii, Erik Vee, Jian Yang
2012	J	`jnl`	Scalable K-Means++ CoRR Bahman Bahmani, Benjamin Moseley, Andrea Vattani, Ravi Kumar, Sergei Vassilvitskii
2012	J	`jnl`	Scalable K-Means++. Proc. VLDB Endow. Bahman Bahmani, Benjamin Moseley, Andrea Vattani, Ravi Kumar, Sergei Vassilvitskii
2012	A*	`conf`	To match or not to match: economics of cookie matching in online advertising. EC Mohammad Mahdian, Arpita Ghosh, R. Preston McAfee, Sergei Vassilvitskii
2011	A*	`conf`	Counting triangles and the curse of the last reducer. WWW Siddharth Suri, Sergei Vassilvitskii
2011	A	`conf`	Cross-Validation and Mean-Square Stability. ICS Satyen Kale, Ravi Kumar, Sergei Vassilvitskii
2011	A	`conf`	Efficiently encoding term co-occurrences in inverted indexes. CIKM Marcus Fontoura, Maxim Gurevich, Vanja Josifovski, Sergei Vassilvitskii
2011	A*	`conf`	Efficiently evaluating graph constraints in content-based publish/subscribe. WWW Andrei Z. Broder, Shirshanka Das, Marcus Fontoura, Bhaskar Ghosh, Vanja Josifovski, Jayavel Shanmugasundaram, Sergei Vassilvitskii
2011	J	`jnl`	Factorization-based Lossless Compression of Inverted Indices CoRR George Beskales, Marcus Fontoura, Maxim Gurevich, Sergei Vassilvitskii, Vanja Josifovski
2011	A	`conf`	Factorization-based lossless compression of inverted indices. CIKM George Beskales, Marcus Fontoura, Maxim Gurevich, Sergei Vassilvitskii, Vanja Josifovski
2011	B	`conf`	Filtering: a method for solving graph problems in MapReduce. SPAA Silvio Lattanzi, Benjamin Moseley, Siddharth Suri, Sergei Vassilvitskii
2011	A*	`conf`	Hiring a secretary from a poset. EC Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii, Andrea Vattani
2011	J	`jnl`	Optimal Envy-Free Pricing with Metric Substitutability. SIAM J. Comput. Ning Chen, Arpita Ghosh, Sergei Vassilvitskii
2011	B	`conf`	The Multiple Attribution Problem in Pay-Per-Conversion Advertising. SAGT Patrick R. Jordan, Mohammad Mahdian, Sergei Vassilvitskii, Erik Vee
2010	A*	`conf`	A Model of Computation for MapReduce. SODA Howard J. Karloff, Siddharth Suri, Sergei Vassilvitskii
2010	—	`conf`	Efficiently evaluating complex boolean expressions. SIGMOD Conference Marcus Fontoura, Suhas Sadanandan, Jayavel Shanmugasundaram, Sergei Vassilvitskii, Erik Vee, Srihari Venkatesan, Jason Y. Zien
2010	A*	`conf`	Finding the Jaccard Median. SODA Flavio Chierichetti, Ravi Kumar, Sandeep Pandey, Sergei Vassilvitskii
2010	A*	`conf`	Generalized distances between rankings. WWW Ravi Kumar, Sergei Vassilvitskii
2010	J	`jnl`	Inventory Allocation for Online Graphical Display Advertising CoRR Jian Yang, Erik Vee, Sergei Vassilvitskii, John A. Tomlin, Jayavel Shanmugasundaram, Tasos Anastasakos, Oliver Kennedy
2010	A*	`conf`	Optimal online assignment with forecasts. EC Erik Vee, Sergei Vassilvitskii, Jayavel Shanmugasundaram
2009	A*	`conf`	Adaptive bidding for display advertising. WWW Arpita Ghosh, Benjamin I. P. Rubinstein, Sergei Vassilvitskii, Martin Zinkevich
2009	J	`jnl`	Battling Predictability and Overconcentration in Recommender Systems. IEEE Data Eng. Bull. Sihem Amer-Yahia, Laks V. S. Lakshmanan, Sergei Vassilvitskii, Cong Yu
2009	J	`jnl`	Bidding for Representative Allocations for Display Advertising CoRR Arpita Ghosh, Randolph Preston McAfee, Kishore Papineni, Sergei Vassilvitskii
2009	—	`conf`	Bidding for Representative Allocations for Display Advertising. WINE Arpita Ghosh, Randolph Preston McAfee, Kishore Papineni, Sergei Vassilvitskii
2009	—	`conf`	Contract Auctions for Sponsored Search. WINE Sharad Goel, Sébastien Lahaie, Sergei Vassilvitskii
2009	A	`conf`	Getting recommender systems to think outside the box. RecSys Zeinab Abbassi, Sihem Amer-Yahia, Laks V. S. Lakshmanan, Sergei Vassilvitskii, Cong Yu
2009	J	`jnl`	Impression-plus-click auctions. SIGecom Exch. Sharad Goel, Sébastien Lahaie, Sergei Vassilvitskii
2009	J	`jnl`	Indexing Boolean Expressions. Proc. VLDB Endow. Steven Whang, Chad Brower, Jayavel Shanmugasundaram, Sergei Vassilvitskii, Erik Vee, Ramana Yerneni, Hector Garcia-Molina
2009	A*	`conf`	Nearest-neighbor caching for content-match applications. WWW Sandeep Pandey, Andrei Z. Broder, Flavio Chierichetti, Vanja Josifovski, Ravi Kumar, Sergei Vassilvitskii
2009	A*	`conf`	Similarity caching. PODS Flavio Chierichetti, Ravi Kumar, Sergei Vassilvitskii
2009	J	`jnl`	Social Networks and Stable Matchings in the Job Market CoRR Esteban Arcaute, Sergei Vassilvitskii
2009	—	`conf`	Social Networks and Stable Matchings in the Job Market. WINE Esteban Arcaute, Sergei Vassilvitskii
2009	J	`jnl`	The Hiring Problem and Lake Wobegon Strategies. SIAM J. Comput. Andrei Z. Broder, Adam Kirsch, Ravi Kumar, Michael Mitzenmacher, Eli Upfal, Sergei Vassilvitskii
2009	A	`conf`	Top- WSDM Ravi Kumar, Kunal Punera, Torsten Suel, Sergei Vassilvitskii
2009	J	`jnl`	Worst-Case and Smoothed Analysis of the ICP Algorithm, with an Application to the k-Means Method. SIAM J. Comput. David Arthur, Sergei Vassilvitskii
2008	A*	`conf`	Optimal envy-free pricing with metric substitutability. EC Ning Chen, Arpita Ghosh, Sergei Vassilvitskii
2008	J	`jnl`	Relaxation in text search using taxonomies. Proc. VLDB Endow. Marcus Fontoura, Vanja Josifovski, Ravi Kumar, Christopher Olston, Andrew Tomkins, Sergei Vassilvitskii
2008	—	`conf`	Sponsored Search Auctions with Reserve Prices: Going Beyond Separability. WINE Rica Gonen, Sergei Vassilvitskii
2008	A*	`conf`	The hiring problem and Lake Wobegon strategies. SODA Andrei Z. Broder, Adam Kirsch, Ravi Kumar, Michael Mitzenmacher, Eli Upfal, Sergei Vassilvitskii
2007	—	`—`	K-means: algorithms, analyses, experiments. Sergei Vassilvitskii
2007	A*	`conf`	On threshold behavior in query incentive networks. EC Esteban Arcaute, Adam Kirsch, Ravi Kumar, David Liben-Nowell, Sergei Vassilvitskii
2007	—	`conf`	Tracing the Path: New Model and Algorithms for Collaborative Filtering. ICDE Workshops Rajeev Motwani, Sergei Vassilvitskii
2007	A*	`conf`	k-means++: the advantages of careful seeding. SODA David Arthur, Sergei Vassilvitskii
2006	—	`conf`	Distinct Values Estimators for Power Law Distributions. ANALCO Rajeev Motwani, Sergei Vassilvitskii
2006	—	`conf`	How slow is the SCG David Arthur, Sergei Vassilvitskii
2006	A*	`conf`	Using web-graph distance for relevance feedback in web search. SIGIR Sergei Vassilvitskii, Eric Brill
2006	A*	`conf`	Worst-case and Smoothed Analysis of the ICP Algorithm, with an Application to the k-means Method. FOCS David Arthur, Sergei Vassilvitskii
2005	J	`jnl`	Efficiently computing succinct trade-off curves. Theor. Comput. Sci. Sergei Vassilvitskii, Mihalis Yannakakis
2004	A*	`conf`	Efficiently Computing Succinct Trade-Off Curves. ICALP Sergei Vassilvitskii, Mihalis Yannakakis
2002	A*	`conf`	A Complete, Local and Parallel Reconfiguration Algorithm for Cube Style Modular Robots. ICRA Sergei Vassilvitskii, Mark Yim, John W. Suh
2002	A*	`conf`	On the General Reconfiguration Problem for Expanding Cube Style Modular Robots. ICRA Sergei Vassilvitskii, Jeremy Kubica, Eleanor Gilbert Rieffel, John W. Suh, Mark Yim