Sergei Vassilvitskii
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
78
Venues
25
Active years
2002–2025
Best venue rank
A*
Where they publish
- A*WWW12 papers
- A*ICML10 papers
- A*KDD7 papers
- A*SODA7 papers
- AAISTATS6 papers
- AWSDM6 papers
- ACIKM3 papers
- BSPAA3 papers
- BSAGT3 papers
- A*ICLR2 papers
- A*FOCS2 papers
- A*PODS2 papers
- BCLOUD2 papers
- A*ICRA2 papers
- A*EMNLP1 paper
- A*ACL1 paper
- NationalITA1 paper
- BWADS1 paper
- CICORES1 paper
- A*INFOCOM1 paper
- A*SIGMOD1 paper
- ARecSys1 paper
- A*ICDE1 paper
- A*SIGIR1 paper
- A*ICALP1 paper
Papers
78 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Scaling Laws for Downstream Task Performance in Machine Translation. | Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo |
| 2025 | KDD | Differentially Private Synthetic Data Release for Topics API Outputs. | Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Andrs Muoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong |
| 2025 | KDD | SPARTA: An Optimization Framework for Differentially Private Sparse Fine-Tuning. | Mehdi Makni, Kayhan Behdin, Gabriel Afriat, Zheng Xu, Sergei Vassilvitskii, Natalia Ponomareva, Rahul Mazumder, Hussein Hazimeh |
| 2025 | SODA | Almost Tight Bounds for Differentially Private Densest Subgraph. | Michael Dinitz, Satyen Kale, Silvio Lattanzi, Sergei Vassilvitskii |
| 2024 | EMNLP | Private prediction for large-scale synthetic text generation. | Kareem Amin, Alex Bie, Weiwei Kong, Alexey Kurakin, Natalia Ponomareva, Umar Syed, Andreas Terzis, Sergei Vassilvitskii |
| 2024 | SODA | Controlling Tail Risk in Online Ski-Rental. | Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii |
| 2023 | ICLR | Easy Differentially Private Linear Regression. | Kareem Amin, Matthew Joseph, Mnica Ribero, Sergei Vassilvitskii |
| 2023 | ICML | Label differential privacy and private training data release. | Rbert Istvan Busa-Fekete, Andrs Muoz Medina, Umar Syed, Sergei Vassilvitskii |
| 2023 | ICML | Predictive Flows for Faster Ford-Fulkerson. | Sami Davies, Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang |
| 2023 | ICML | Learning-augmented private algorithms for multiple quantile release. | Mikhail Khodak, Kareem Amin, Travis Dick, Sergei Vassilvitskii |
| 2023 | ICML | Speeding Up Bellman Ford via Minimum Violation Permutations. | Silvio Lattanzi, Ola Svensson, Sergei Vassilvitskii |
| 2023 | KDD | How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy. | Natalia Ponomareva, Sergei Vassilvitskii, Zheng Xu, Brendan McMahan, Alexey Kurakin, Chiyaun Zhang |
| 2022 | ACL | Training Text-to-Text Transformers with Privacy Guarantees. | Natalia Ponomareva, Jasmijn Bastings, Sergei Vassilvitskii |
| 2022 | AISTATS | Label differential privacy via clustering. | Hossein Esfandiari, Vahab S. Mirrokni, Umar Syed, Sergei Vassilvitskii |
| 2022 | KDD | Scalable Differentially Private Clustering via Hierarchically Separated Trees. | Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab Mirrokni, Andres Muoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii |
| 2021 | AISTATS | Hierarchical Clustering in General Metric Spaces using Approximate Nearest Neighbors. | Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang |
| 2021 | AISTATS | Private optimization without constraint violations. | Andrs Muoz Medina, Umar Syed, Sergei Vassilvitskii, Ellen Vitercik |
| 2021 | KDD | Clustering for Private Interest-based Advertising. | Alessandro Epasto, Andrs Muoz Medina, Steven Avery, Yijian Bai, Rbert 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 |
| 2020 | ITA | Residual Based Sampling for Online Low Rank Approximation. | Aditya Bhaskara, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam |
| 2020 | SODA | Online Scheduling via Learned Weights. | Silvio Lattanzi, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii |
| 2019 | AISTATS | Matroids, Matchings, and Fairness. | Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii |
| 2019 | AISTATS | Consistent Online Optimization: Convex and Submodular. | Mohammad Reza Karimi Jaghargh, Andreas Krause, Silvio Lattanzi, Sergei Vassilvitskii |
| 2019 | FOCS | Residual Based Sampling for Online Low Rank Approximation. | Aditya Bhaskara, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam |
| 2019 | ICML | Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy. | Kareem Amin, Alex Kulesza, Andres Muoz Medina, Sergei Vassilvitskii |
| 2019 | ICML | A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes. | Jennifer Gillenwater, Alex Kulesza, Zelda Mariet, Sergei Vassilvitskii |
| 2019 | PODS | Better Sliding Window Algorithms to Maximize Subadditive and Diversity Objectives. | Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam |
| 2018 | CIKM | Online Learning for Non-Stationary A/B Tests. | Andrs Muoz Medina, Sergei Vassilvitskii, Dong Yin |
| 2018 | ICML | Competitive Caching with Machine Learned Advice. | Thodoris Lykouris, Sergei Vassilvitskii |
| 2018 | WWW | Testing Incentive Compatibility in Display Ad Auctions. | Sbastien Lahaie, Andrs Muoz Medina, Balasubramanian Sivan, Sergei Vassilvitskii |
| 2017 | CLOUD | SQML: large-scale in-database machine learning with pure SQL. | Umar Syed, Sergei Vassilvitskii |
| 2017 | ICML | Consistent k-Clustering. | Silvio Lattanzi, Sergei Vassilvitskii |
| 2017 | WWW | Indexing Public-Private Graphs. | Aaron Archer, Silvio Lattanzi, Peter Likarish, Sergei Vassilvitskii |
| 2017 | WWW | Submodular Optimization Over Sliding Windows. | Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam |
| 2016 | AISTATS | Sketching, Embedding and Dimensionality Reduction in Information Theoretic Spaces. | Amirali Abdullah, Ravi Kumar, Andrew McGregor, Sergei Vassilvitskii, Suresh Venkatasubramanian |
| 2016 | ICML | Pricing a Low-regret Seller. | Hoda Heidari, Mohammad Mahdian, Umar Syed, Sergei Vassilvitskii, Sadra Yazdanbod |
| 2016 | WWW | A Field Guide to Personalized Reserve Prices. | Renato Paes Leme, Martin Pl, Sergei Vassilvitskii |
| 2016 | SPAA | Shuffles and Circuits: (On Lower Bounds for Modern Parallel Computation). | Tim Roughgarden, Sergei Vassilvitskii, Joshua R. Wang |
| 2015 | KDD | Algorithmic Cartography: Placing Points of Interest and Ads on Maps. | Mohammad Mahdian, Okke Schrijvers, Sergei Vassilvitskii |
| 2015 | WSDM | Driven by Food: Modeling Geographic Choice. | Ravi Kumar, Mohammad Mahdian, Bo Pang, Andrew Tomkins, Sergei Vassilvitskii |
| 2015 | WSDM | Inverting a Steady-State. | Ravi Kumar, Andrew Tomkins, Sergei Vassilvitskii, Erik Vee |
| 2014 | CLOUD | Connected Components in MapReduce and Beyond. | Raimondas Kiveris, Silvio Lattanzi, Vahab S. Mirrokni, Vibhor Rastogi, Sergei Vassilvitskii |
| 2014 | WWW | The dynamics of repeat consumption. | Ashton Anderson, Ravi Kumar, Andrew Tomkins, Sergei Vassilvitskii |
| 2014 | WWW | Advertising in a stream. | Samuel Ieong, Mohammad Mahdian, Sergei Vassilvitskii |
| 2014 | WSDM | Scalable K-Means by ranked retrieval. | Andrei Z. Broder, Lluis Garcia Pueyo, Vanja Josifovski, Sergei Vassilvitskii, Srihari Venkatesan |
| 2014 | SAGT | Value of Targeting. | Kshipra Bhawalkar, Patrick Hummel, Sergei Vassilvitskii |
| 2013 | ICML | Near-Optimal Bounds for Cross-Validation via Loss Stability. | Ravi Kumar, Daniel Lokshtanov, Sergei Vassilvitskii, Andrea Vattani |
| 2013 | WSDM | Sharding social networks. | Quang Duong, Sharad Goel, Jake M. Hofman, Sergei Vassilvitskii |
| 2013 | WSDM | Rank quantization. | Ravi Kumar, Ronny Lempel, Roy Schwartz, Sergei Vassilvitskii |
| 2013 | SPAA | Fast greedy algorithms in mapreduce and streaming. | Ravi Kumar, Benjamin Moseley, Sergei Vassilvitskii, Andrea Vattani |
| 2013 | WADS | MapReduce Algorithmics. | Sergei Vassilvitskii |
| 2012 | ICORES | Inventory Allocation for Online Graphical Display Advertising using Multi-objective Optimization. | Jian Yang, Erik Vee, Sergei Vassilvitskii, John A. Tomlin, Jayavel Shanmugasundaram, Tasos Anastasakos, Oliver Kennedy |
| 2012 | INFOCOM | Ad auctions with data. | Hu Fu, Patrick R. Jordan, Mohammad Mahdian, Uri Nadav, Inbal Talgam-Cohen, Sergei Vassilvitskii |
| 2012 | KDD | SHALE: an efficient algorithm for allocation of guaranteed display advertising. | Vijay Bharadwaj, Peiji Chen, Wenjing Ma, Chandrashekhar Nagarajan, John A. Tomlin, Sergei Vassilvitskii, Erik Vee, Jian Yang |
| 2012 | WWW | Handling forecast errors while bidding for display advertising. | Kevin J. Lang, Benjamin Moseley, Sergei Vassilvitskii |
| 2012 | SAGT | Ad Auctions with Data. | Hu Fu, Patrick R. Jordan, Mohammad Mahdian, Uri Nadav, Inbal Talgam-Cohen, Sergei Vassilvitskii |
| 2011 | CIKM | Factorization-based lossless compression of inverted indices. | George Beskales, Marcus Fontoura, Maxim Gurevich, Sergei Vassilvitskii, Vanja Josifovski |
| 2011 | CIKM | Efficiently encoding term co-occurrences in inverted indexes. | Marcus Fontoura, Maxim Gurevich, Vanja Josifovski, Sergei Vassilvitskii |
| 2011 | WWW | Efficiently evaluating graph constraints in content-based publish/subscribe. | Andrei Z. Broder, Shirshanka Das, Marcus Fontoura, Bhaskar Ghosh, Vanja Josifovski, Jayavel Shanmugasundaram, Sergei Vassilvitskii |
| 2011 | WWW | Counting triangles and the curse of the last reducer. | Siddharth Suri, Sergei Vassilvitskii |
| 2011 | SPAA | Filtering: a method for solving graph problems in MapReduce. | Silvio Lattanzi, Benjamin Moseley, Siddharth Suri, Sergei Vassilvitskii |
| 2011 | SAGT | The Multiple Attribution Problem in Pay-Per-Conversion Advertising. | Patrick R. Jordan, Mohammad Mahdian, Sergei Vassilvitskii, Erik Vee |
| 2010 | WWW | Generalized distances between rankings. | Ravi Kumar, Sergei Vassilvitskii |
| 2010 | SIGMOD | Efficiently evaluating complex boolean expressions. | Marcus Fontoura, Suhas Sadanandan, Jayavel Shanmugasundaram, Sergei Vassilvitskii, Erik Vee, Srihari Venkatesan, Jason Y. Zien |
| 2010 | SODA | Finding the Jaccard Median. | Flavio Chierichetti, Ravi Kumar, Sandeep Pandey, Sergei Vassilvitskii |
| 2010 | SODA | A Model of Computation for MapReduce. | Howard J. Karloff, Siddharth Suri, Sergei Vassilvitskii |
| 2009 | PODS | Similarity caching. | Flavio Chierichetti, Ravi Kumar, Sergei Vassilvitskii |
| 2009 | RecSys | Getting recommender systems to think outside the box. | Zeinab Abbassi, Sihem Amer-Yahia, Laks V. S. Lakshmanan, Sergei Vassilvitskii, Cong Yu |
| 2009 | WWW | Adaptive bidding for display advertising. | Arpita Ghosh, Benjamin I. P. Rubinstein, Sergei Vassilvitskii, Martin Zinkevich |
| 2009 | WWW | Nearest-neighbor caching for content-match applications. | Sandeep Pandey, Andrei Z. Broder, Flavio Chierichetti, Vanja Josifovski, Ravi Kumar, Sergei Vassilvitskii |
| 2009 | WSDM | Top- | Ravi Kumar, Kunal Punera, Torsten Suel, Sergei Vassilvitskii |
| 2008 | SODA | The hiring problem and Lake Wobegon strategies. | Andrei Z. Broder, Adam Kirsch, Ravi Kumar, Michael Mitzenmacher, Eli Upfal, Sergei Vassilvitskii |
| 2007 | ICDE | Tracing the Path: New Model and Algorithms for Collaborative Filtering. | Rajeev Motwani, Sergei Vassilvitskii |
| 2007 | SODA | k-means++: the advantages of careful seeding. | David Arthur, Sergei Vassilvitskii |
| 2006 | FOCS | Worst-case and Smoothed Analysis of the ICP Algorithm, with an Application to the k-means Method. | David Arthur, Sergei Vassilvitskii |
| 2006 | SIGIR | Using web-graph distance for relevance feedback in web search. | Sergei Vassilvitskii, Eric Brill |
| 2004 | ICALP | Efficiently Computing Succinct Trade-Off Curves. | Sergei Vassilvitskii, Mihalis Yannakakis |
| 2002 | ICRA | On the General Reconfiguration Problem for Expanding Cube Style Modular Robots. | Sergei Vassilvitskii, Jeremy Kubica, Eleanor Gilbert Rieffel, John W. Suh, Mark Yim |
| 2002 | ICRA | A Complete, Local and Parallel Reconfiguration Algorithm for Cube Style Modular Robots. | Sergei Vassilvitskii, Mark Yim, John W. Suh |