Timezone: »
Poster
Sliding Window Algorithms for k-Clustering Problems
Michele Borassi · Alessandro Epasto · Silvio Lattanzi · Sergei Vassilvitskii · Morteza Zadimoghaddam
The sliding window model of computation captures scenarios in which data is arriving continuously, but only the latest $w$ elements should be used for analysis. The goal is to design algorithms that update the solution efficiently with each arrival rather than recomputing it from scratch. In this work, we focus on $k$-clustering problems such as $k$-means and $k$-median. In this setting, we provide simple and practical algorithms that offer stronger performance guarantees than previous results. Empirically, we show that our methods store only a small fraction of the data, are orders of magnitude faster, and find solutions with costs only slightly higher than those returned by algorithms with access to the full dataset.
Author Information
Michele Borassi (Google Switzerland GmbH)
Alessandro Epasto (Google)

I am a staff research scientist at Google, New York working in the Google Research Algorithms and Optimization team lead by Vahab Mirrokni. I received a Ph.D in computer science from Sapienza University of Rome, where I was advised by Professor Alessandro Panconesi and supported by the Google Europe Ph.D. Fellowship in Algorithms, 2011. I was also a post-doc at the department of computer science of Brown University in Providence (RI), USA where I was advised by Professor Eli Upfal. My research interests include algorithmic problems in machine learning and data mining, in particular in the areas of clustering, privacy, and large scale graphs analysis.
Silvio Lattanzi (Google Research)
Sergei Vassilvitskii (Google)
Morteza Zadimoghaddam (Google Research)
More from the Same Authors
-
2022 : Scalable and Improved Algorithms for Individually Fair Clustering »
Mohammadhossein Bateni · Vincent Cohen-Addad · Alessandro Epasto · Silvio Lattanzi -
2022 : Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank »
Alessandro Epasto · Vahab Mirrokni · Bryan Perozzi · Anton Tsitsulin · Peilin Zhong -
2022 Poster: Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank »
Alessandro Epasto · Vahab Mirrokni · Bryan Perozzi · Anton Tsitsulin · Peilin Zhong -
2022 Poster: Active Learning of Classifiers with Label and Seed Queries »
Marco Bressan · Nicolò Cesa-Bianchi · Silvio Lattanzi · Andrea Paudice · Maximilian Thiessen -
2022 Poster: Near-Optimal Correlation Clustering with Privacy »
Vincent Cohen-Addad · Chenglin Fan · Silvio Lattanzi · Slobodan Mitrovic · Ashkan Norouzi-Fard · Nikos Parotsidis · Jakub Tarnawski -
2022 Poster: Near-Optimal Private and Scalable $k$-Clustering »
Vincent Cohen-Addad · Alessandro Epasto · Vahab Mirrokni · Shyam Narayanan · Peilin Zhong -
2022 Poster: Efficient and Stable Fully Dynamic Facility Location »
Sayan Bhattacharya · Silvio Lattanzi · Nikos Parotsidis -
2021 Poster: Online Facility Location with Multiple Advice »
Matteo Almanza · Flavio Chierichetti · Silvio Lattanzi · Alessandro Panconesi · Giuseppe Re -
2021 Poster: Robust Online Correlation Clustering »
Silvio Lattanzi · Benjamin Moseley · Sergei Vassilvitskii · Yuyan Wang · Rudy Zhou -
2021 Poster: Parallel and Efficient Hierarchical k-Median Clustering »
Vincent Cohen-Addad · Silvio Lattanzi · Ashkan Norouzi-Fard · Christian Sohler · Ola Svensson -
2021 Poster: Efficient and Local Parallel Random Walks »
Michael Kapralov · Silvio Lattanzi · Navid Nouri · Jakab Tardos -
2021 Poster: On Margin-Based Cluster Recovery with Oracle Queries »
Marco Bressan · Nicolò Cesa-Bianchi · Silvio Lattanzi · Andrea Paudice -
2020 Poster: Fully Dynamic Algorithm for Constrained Submodular Optimization »
Silvio Lattanzi · Slobodan Mitrović · Ashkan Norouzi-Fard · Jakub Tarnawski · Morteza Zadimoghaddam -
2020 Oral: Fully Dynamic Algorithm for Constrained Submodular Optimization »
Silvio Lattanzi · Slobodan Mitrović · Ashkan Norouzi-Fard · Jakub Tarnawski · Morteza Zadimoghaddam -
2020 Poster: Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions »
Alessandro Epasto · Mohammad Mahdian · Vahab Mirrokni · Emmanouil Zampetakis -
2020 Spotlight: Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions »
Alessandro Epasto · Mohammad Mahdian · Vahab Mirrokni · Emmanouil Zampetakis -
2020 Poster: Fair Hierarchical Clustering »
Sara Ahmadian · Alessandro Epasto · Marina Knittel · Ravi Kumar · Mohammad Mahdian · Benjamin Moseley · Philip Pham · Sergei Vassilvitskii · Yuyan Wang -
2020 Poster: Fast and Accurate $k$-means++ via Rejection Sampling »
Vincent Cohen-Addad · Silvio Lattanzi · Ashkan Norouzi-Fard · Christian Sohler · Ola Svensson -
2020 Poster: Online MAP Inference of Determinantal Point Processes »
Aditya Bhaskara · Amin Karbasi · Silvio Lattanzi · Morteza Zadimoghaddam -
2020 Poster: Exact Recovery of Mangled Clusters with Same-Cluster Queries »
Marco Bressan · Nicolò Cesa-Bianchi · Silvio Lattanzi · Andrea Paudice -
2020 Poster: Smoothly Bounding User Contributions in Differential Privacy »
Alessandro Epasto · Mohammad Mahdian · Jieming Mao · Vahab Mirrokni · Lijie Ren -
2020 Oral: Exact Recovery of Mangled Clusters with Same-Cluster Queries »
Marco Bressan · Nicolò Cesa-Bianchi · Silvio Lattanzi · Andrea Paudice -
2020 Session: Orals & Spotlights Track 05: Clustering/Ranking »
Silvio Lattanzi · Katerina Fragkiadaki -
2020 : Learning Multiple Embeddings »
Alessandro Epasto -
2020 : Similarity Ranking »
Alessandro Epasto -
2020 : Application Story: Privacy »
Alessandro Epasto -
2019 : Coffee Break & Poster Session 2 »
Juho Lee · Yoonho Lee · Yee Whye Teh · Raymond A. Yeh · Yuan-Ting Hu · Alex Schwing · Sara Ahmadian · Alessandro Epasto · Marina Knittel · Ravi Kumar · Mohammad Mahdian · Christian Bueno · Aditya Sanghi · Pradeep Kumar Jayaraman · Ignacio Arroyo-Fernández · Andrew Hryniowski · Vinayak Mathur · Sanjay Singh · Shahrzad Haddadan · Vasco Portilheiro · Luna Zhang · Mert Yuksekgonul · Jhosimar Arias Figueroa · Deepak Maurya · Balaraman Ravindran · Frank NIELSEN · Philip Pham · Justin Payan · Andrew McCallum · Jinesh Mehta · Ke SUN -
2019 : Contributed Talk - Fair Hierarchical Clustering »
Sara Ahmadian · Alessandro Epasto · Marina Knittel · Ravi Kumar · Mohammad Mahdian · Philip Pham -
2019 : Coffee Break & Poster Session 1 »
Yan Zhang · Jonathon Hare · Adam Prugel-Bennett · Po Leung · Patrick Flaherty · Pitchaya Wiratchotisatian · Alessandro Epasto · Silvio Lattanzi · Sergei Vassilvitskii · Morteza Zadimoghaddam · Theja Tulabandhula · Fabian Fuchs · Adam Kosiorek · Ingmar Posner · William Hang · Anna Goldie · Sujith Ravi · Azalia Mirhoseini · Yuwen Xiong · Mengye Ren · Renjie Liao · Raquel Urtasun · Haici Zhang · Michele Borassi · Shengda Luo · Andrew Trapp · Geoffroy Dubourg-Felonneau · Yasmeen Kussad · Christopher Bender · Manzil Zaheer · Junier Oliva · Michał Stypułkowski · Maciej Zieba · Austin Dill · Chun-Liang Li · Songwei Ge · Eunsu Kang · Oiwi Parker Jones · Kelvin Ka Wing Wong · Joshua Payne · Yang Li · Azade Nazi · Erkut Erdem · Aykut Erdem · Kevin O'Connor · Juan J Garcia · Maciej Zamorski · Jan Chorowski · Deeksha Sinha · Harry Clifford · John W Cassidy -
2019 Poster: Differentially Private Covariance Estimation »
Kareem Amin · Travis Dick · Alex Kulesza · Andres Munoz Medina · Sergei Vassilvitskii -
2018 Poster: Mallows Models for Top-k Lists »
Flavio Chierichetti · Anirban Dasgupta · Shahrzad Haddadan · Ravi Kumar · Silvio Lattanzi -
2018 Poster: Maximizing Induced Cardinality Under a Determinantal Point Process »
Jennifer Gillenwater · Alex Kulesza · Sergei Vassilvitskii · Zelda Mariet -
2017 Poster: Revenue Optimization with Approximate Bid Predictions »
Andres Munoz Medina · Sergei Vassilvitskii -
2017 Poster: Fair Clustering Through Fairlets »
Flavio Chierichetti · Ravi Kumar · Silvio Lattanzi · Sergei Vassilvitskii -
2017 Spotlight: Fair Clustering Through Fairlets »
Flavio Chierichetti · Ravi Kumar · Silvio Lattanzi · Sergei Vassilvitskii -
2017 Poster: Statistical Cost Sharing »
Eric Balkanski · Umar Syed · Sergei Vassilvitskii -
2017 Poster: Affinity Clustering: Hierarchical Clustering at Scale »
Mohammadhossein Bateni · Soheil Behnezhad · Mahsa Derakhshan · MohammadTaghi Hajiaghayi · Raimondas Kiveris · Silvio Lattanzi · Vahab Mirrokni -
2016 Poster: On Mixtures of Markov Chains »
Rishi Gupta · Ravi Kumar · Sergei Vassilvitskii -
2016 Poster: Fast Distributed Submodular Cover: Public-Private Data Summarization »
Baharan Mirzasoleiman · Morteza Zadimoghaddam · Amin Karbasi -
2016 Poster: Community Detection on Evolving Graphs »
Stefano Leonardi · Aris Anagnostopoulos · Jakub Łącki · Silvio Lattanzi · Mohammad Mahdian -
2014 Poster: Distributed Balanced Clustering via Mapping Coresets »
Mohammadhossein Bateni · Aditya Bhaskara · Silvio Lattanzi · Vahab Mirrokni