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ORCIDSilvio Lattanzi
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- affiliation: Google Research, Zurich, Switzerland
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Journal Articles
- 2024
[j12]T.-H. Hubert Chan, Silvio Lattanzi, Mauro Sozio, Bo Wang:
Fully Dynamic k-Center Clustering with Outliers. Algorithmica 86(1): 171-193 (2024)- [j11]Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice:
Margin-Based Active Learning of Classifiers. J. Mach. Learn. Res. 25: 127:1-127:45 (2024) - [j10]Paul Dütting
, Silvio Lattanzi, Renato Paes Leme, Sergei Vassilvitskii:
Secretaries with Advice. Math. Oper. Res. 49(2): 856-879 (2024) - 2023
- [j9]Sungjin Im, Ravi Kumar, Silvio Lattanzi, Benjamin Moseley, Sergei Vassilvitskii:
Massively Parallel Computation: Algorithms and Applications. Found. Trends Optim. 5(4): 340-417 (2023) - 2019
- [j8]Mohammad Hossein Bateni, Mohammad Taghi Hajiaghayi, Silvio Lattanzi:
Introduction to the Special Issue for SPAA'17. ACM Trans. Parallel Comput. 6(3): 10:1 (2019) - 2018
- [j7]Flavio Chierichetti, George Giakkoupis, Silvio Lattanzi, Alessandro Panconesi:
Rumor Spreading and Conductance. J. ACM 65(4): 17:1-17:21 (2018) - 2016
- [j6]Silvio Lattanzi, Stefano Leonardi:
Efficient computation of the Weighted Clustering Coefficient. Internet Math. 12(6): 381-401 (2016) - 2015
- [j5]Alessandro Epasto, Silvio Lattanzi, Vahab S. Mirrokni, Ismail Sebe, Ahmed Taei, Sunita Verma:
Ego-net Community Mining Applied to Friend Suggestion. Proc. VLDB Endow. 9(4): 324-335 (2015) - 2014
- [j4]Lorenzo Alvisi, Allen Clement, Alessandro Epasto, Silvio Lattanzi, Alessandro Panconesi:
Communities, Random Walks, and Social Sybil Defense. Internet Math. 10(3-4): 360-420 (2014) - [j3]Nitish Korula, Silvio Lattanzi:
An efficient reconciliation algorithm for social networks. Proc. VLDB Endow. 7(5): 377-388 (2014) - 2013
- [j2]Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Alessandro Panconesi, Prabhakar Raghavan:
Models for the Compressible Web. SIAM J. Comput. 42(5): 1777-1802 (2013) - 2011
- [j1]Flavio Chierichetti, Silvio Lattanzi, Alessandro Panconesi:
Rumor spreading in social networks. Theor. Comput. Sci. 412(24): 2602-2610 (2011)
Conference and Workshop Papers
- 2024
- [c89]MohammadHossein Bateni, Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi:
A Scalable Algorithm for Individually Fair k-Means Clustering. AISTATS 2024: 3151-3159 - [c88]Vincent Cohen-Addad, Silvio Lattanzi, Andreas Maggiori, Nikos Parotsidis:
Dynamic Correlation Clustering in Sublinear Update Time. ICML 2024 - [c87]Vincent Cohen-Addad, Tommaso d'Orsi, Silvio Lattanzi, Rajai Nasser:
Multi-View Stochastic Block Models. ICML 2024 - [c86]Paul Duetting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard, Morteza Zadimoghaddam:
Consistent Submodular Maximization. ICML 2024 - [c85]Sara Ahmadian, MohammadHossein Bateni, Hossein Esfandiari, Silvio Lattanzi, Morteza Monemizadeh, Ashkan Norouzi-Fard:
Resilient k-Clustering. KDD 2024: 29-38 - 2023
- [c84]Paul Duetting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard, Morteza Zadimoghaddam:
Fully Dynamic Submodular Maximization over Matroids. ICML 2023: 8821-8835 - [c83]Silvio Lattanzi, Ola Svensson, Sergei Vassilvitskii:
Speeding Up Bellman Ford via Minimum Violation Permutations. ICML 2023: 18584-18598 - [c82]Lorenzo Beretta, Vincent Cohen-Addad, Silvio Lattanzi, Nikos Parotsidis:
Multi-Swap k-Means++. NeurIPS 2023 - [c81]Sayan Bhattacharya, Martín Costa, Silvio Lattanzi, Nikos Parotsidis:
Fully Dynamic k-Clustering in Õ(k) Update Time. NeurIPS 2023 - [c80]Michael Kapralov, Akash Kumar, Silvio Lattanzi, Aida Mousavifar:
Learning Hierarchical Cluster Structure of Graphs in Sublinear Time. SODA 2023: 925-939 - 2022
- [c79]T.-H. Hubert Chan, Silvio Lattanzi, Mauro Sozio, Bo Wang:
Fully Dynamic k-Center Clustering with Outliers. COCOON 2022: 150-161 - [c78]Buddhima Gamlath, Silvio Lattanzi, Ashkan Norouzi-Fard, Ola Svensson:
Approximate Cluster Recovery from Noisy Labels. COLT 2022: 1463-1509 - [c77]Vincent Cohen-Addad, Silvio Lattanzi, Andreas Maggiori, Nikos Parotsidis:
Online and Consistent Correlation Clustering. ICML 2022: 4157-4179 - [c76]Paul Duetting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard, Morteza Zadimoghaddam:
Deletion Robust Submodular Maximization over Matroids. ICML 2022: 5671-5693 - [c75]Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab Mirrokni, Andres Muñoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii:
Scalable Differentially Private Clustering via Hierarchically Separated Trees. KDD 2022: 221-230 - [c74]Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice, Maximilian Thiessen:
Active Learning of Classifiers with Label and Seed Queries. NeurIPS 2022 - [c73]Sayan Bhattacharya, Silvio Lattanzi, Nikos Parotsidis:
Efficient and Stable Fully Dynamic Facility Location. NeurIPS 2022 - [c72]Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski:
Near-Optimal Correlation Clustering with Privacy. NeurIPS 2022 - [c71]Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi:
The Gibbs-Rand Model. PODS 2022: 151-163 - 2021
- [c70]Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice:
Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries. COLT 2021: 775-803 - [c69]Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski:
Correlation Clustering in Constant Many Parallel Rounds. ICML 2021: 2069-2078 - [c68]Matteo Almanza, Flavio Chierichetti, Silvio Lattanzi, Alessandro Panconesi, Giuseppe Re:
Online Facility Location with Multiple Advice. NeurIPS 2021: 4661-4673 - [c67]Silvio Lattanzi, Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang, Rudy Zhou:
Robust Online Correlation Clustering. NeurIPS 2021: 4688-4698 - [c66]Vincent Cohen-Addad, Silvio Lattanzi, Ashkan Norouzi-Fard, Christian Sohler, Ola Svensson:
Parallel and Efficient Hierarchical k-Median Clustering. NeurIPS 2021: 20333-20345 - [c65]Michael Kapralov, Silvio Lattanzi, Navid Nouri, Jakab Tardos:
Efficient and Local Parallel Random Walks. NeurIPS 2021: 21375-21387 - [c64]Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice:
On Margin-Based Cluster Recovery with Oracle Queries. NeurIPS 2021: 25231-25243 - [c63]Paul Dütting, Silvio Lattanzi, Renato Paes Leme, Sergei Vassilvitskii:
Secretaries with Advice. EC 2021: 409-429 - [c62]Grzegorz Gluch, Michael Kapralov, Silvio Lattanzi, Aida Mousavifar, Christian Sohler:
Spectral Clustering Oracles in Sublinear Time. SODA 2021: 1598-1617 - [c61]Hendrik Fichtenberger, Silvio Lattanzi, Ashkan Norouzi-Fard, Ola Svensson:
Consistent k-Clustering for General Metrics. SODA 2021: 2660-2678 - [c60]Matteo Almanza, Silvio Lattanzi, Alessandro Panconesi, Giuseppe Re:
Twin Peaks, a Model for Recurring Cascades. WWW 2021: 681-692 - 2020
- [c59]Aditya Bhaskara, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Residual Based Sampling for Online Low Rank Approximation. ITA 2020: 1-19 - [c58]Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice:
Exact Recovery of Mangled Clusters with Same-Cluster Queries. NeurIPS 2020 - [c57]Aditya Bhaskara, Amin Karbasi, Silvio Lattanzi, Morteza Zadimoghaddam:
Online MAP Inference of Determinantal Point Processes. NeurIPS 2020 - [c56]Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Sliding Window Algorithms for k-Clustering Problems. NeurIPS 2020 - [c55]Vincent Cohen-Addad, Silvio Lattanzi, Ashkan Norouzi-Fard, Christian Sohler, Ola Svensson:
Fast and Accurate $k$-means++ via Rejection Sampling. NeurIPS 2020 - [c54]Silvio Lattanzi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakub Tarnawski, Morteza Zadimoghaddam:
Fully Dynamic Algorithm for Constrained Submodular Optimization. NeurIPS 2020 - [c53]Silvio Lattanzi, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii:
Online Scheduling via Learned Weights. SODA 2020: 1859-1877 - 2019
- [c52]Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii:
Matroids, Matchings, and Fairness. AISTATS 2019: 2212-2220 - [c51]Mohammad Reza Karimi Jaghargh, Andreas Krause, Silvio Lattanzi, Sergei Vassilvitskii:
Consistent Online Optimization: Convex and Submodular. AISTATS 2019: 2241-2250 - [c50]Aditya Bhaskara, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Residual Based Sampling for Online Low Rank Approximation. FOCS 2019: 1596-1614 - [c49]Mohsen Ghaffari, Silvio Lattanzi, Slobodan Mitrovic:
Improved Parallel Algorithms for Density-Based Network Clustering. ICML 2019: 2201-2210 - [c48]Ehsan Kazemi, Marko Mitrovic, Morteza Zadimoghaddam, Silvio Lattanzi, Amin Karbasi:
Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity. ICML 2019: 3311-3320 - [c47]Silvio Lattanzi, Christian Sohler:
A Better k-means++ Algorithm via Local Search. ICML 2019: 3662-3671 - [c46]Silvio Lattanzi, Thomas Lavastida, Kefu Lu, Benjamin Moseley:
A Framework for Parallelizing Hierarchical Clustering Methods. ECML/PKDD (1) 2019: 73-89 - [c45]Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Better Sliding Window Algorithms to Maximize Subadditive and Diversity Objectives. PODS 2019: 254-268 - [c44]Giuseppe F. Italiano, Silvio Lattanzi, Vahab S. Mirrokni, Nikos Parotsidis:
Dynamic Algorithms for the Massively Parallel Computation Model. SPAA 2019: 49-58 - 2018
- [c43]Olivier Bachem, Mario Lucic, Silvio Lattanzi:
One-shot Coresets: The Case of k-Clustering. AISTATS 2018: 784-792 - [c42]Hossein Esfandiari, Silvio Lattanzi, Vahab S. Mirrokni:
Parallel and Streaming Algorithms for K-Core Decomposition. ICML 2018: 1396-1405 - [c41]Aditya Bhaskara, Silvio Lattanzi:
Non-Negative Sparse Regression and Column Subset Selection with L1 Error. ITCS 2018: 7:1-7:15 - [c40]Flavio Chierichetti, Anirban Dasgupta, Shahrzad Haddadan, Ravi Kumar, Silvio Lattanzi:
Mallows Models for Top-k Lists. NeurIPS 2018: 4387-4397 - 2017
- [c39]Flavio Chierichetti, Sreenivas Gollapudi, Ravi Kumar, Silvio Lattanzi, Rina Panigrahy, David P. Woodruff:
Algorithms for $\ell_p$ Low-Rank Approximation. ICML 2017: 806-814 - [c38]Silvio Lattanzi, Sergei Vassilvitskii:
Consistent k-Clustering. ICML 2017: 1975-1984 - [c37]Alessandro Epasto, Silvio Lattanzi, Renato Paes Leme:
Ego-Splitting Framework: from Non-Overlapping to Overlapping Clusters. KDD 2017: 145-154 - [c36]Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii:
Fair Clustering Through Fairlets. NIPS 2017: 5029-5037 - [c35]MohammadHossein Bateni, Soheil Behnezhad, Mahsa Derakhshan, MohammadTaghi Hajiaghayi, Raimondas Kiveris, Silvio Lattanzi, Vahab S. Mirrokni:
Affinity Clustering: Hierarchical Clustering at Scale. NIPS 2017: 6864-6874 - [c34]Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Submodular Optimization Over Sliding Windows. WWW 2017: 421-430 - [c33]Aaron Archer, Silvio Lattanzi, Peter Likarish, Sergei Vassilvitskii:
Indexing Public-Private Graphs. WWW 2017: 1461-1470 - 2016
- [c32]Aris Anagnostopoulos, Jakub Lacki, Silvio Lattanzi, Stefano Leonardi, Mohammad Mahdian:
Community Detection on Evolving Graphs. NIPS 2016: 3522-3530 - [c31]Zeyuan Allen Zhu, Aditya Bhaskara, Silvio Lattanzi, Vahab S. Mirrokni, Lorenzo Orecchia:
Expanders via Local Edge Flips. SODA 2016: 259-269 - [c30]Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi, Tamás Sarlós:
On Sampling Nodes in a Network. WWW 2016: 471-481 - [c29]Christopher J. Riederer, Yunsung Kim, Augustin Chaintreau, Nitish Korula, Silvio Lattanzi:
Linking Users Across Domains with Location Data: Theory and Validation. WWW 2016: 707-719 - 2015
- [c28]Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi:
On Learning Mixture Models for Permutations. ITCS 2015: 85-92 - [c27]Silvio Lattanzi, Stefano Leonardi, Vahab S. Mirrokni, Ilya P. Razenshteyn:
Robust Hierarchical k-Center Clustering. ITCS 2015: 211-218 - [c26]Flavio Chierichetti, Alessandro Epasto, Ravi Kumar, Silvio Lattanzi, Vahab S. Mirrokni:
Efficient Algorithms for Public-Private Social Networks. KDD 2015: 139-148 - [c25]Silvio Lattanzi, Yaron Singer:
The Power of Random Neighbors in Social Networks. WSDM 2015: 77-86 - [c24]Silvio Lattanzi, Vahab S. Mirrokni:
Distributed Graph Algorithmics: Theory and Practice. WSDM 2015: 419-420 - [c23]Alessandro Epasto, Silvio Lattanzi, Mauro Sozio:
Efficient Densest Subgraph Computation in Evolving Graphs. WWW 2015: 300-310 - 2014
- [c22]Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi:
On Reconstructing a Hidden Permutation. APPROX-RANDOM 2014: 604-617 - [c21]Raimondas Kiveris, Silvio Lattanzi, Vahab S. Mirrokni, Vibhor Rastogi, Sergei Vassilvitskii:
Connected Components in MapReduce and Beyond. SoCC 2014: 18:1-18:13 - [c20]MohammadHossein Bateni, Aditya Bhaskara, Silvio Lattanzi, Vahab S. Mirrokni:
Distributed Balanced Clustering via Mapping Coresets. NIPS 2014: 2591-2599 - [c19]Avner May, Augustin Chaintreau, Nitish Korula, Silvio Lattanzi:
Filter & follow: how social media foster content curation. SIGMETRICS 2014: 43-55 - [c18]Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi:
Learning Entangled Single-Sample Gaussians. SODA 2014: 511-522 - [c17]Silvio Lattanzi, Stefano Leonardi:
Efficient Computation of the Weighted Clustering Coefficient. WAW 2014: 34-46 - [c16]Alessandro Epasto, Jon Feldman, Silvio Lattanzi, Stefano Leonardi, Vahab S. Mirrokni:
Reduce and aggregate: similarity ranking in multi-categorical bipartite graphs. WWW 2014: 349-360 - 2013
- [c15]Zeyuan Allen Zhu, Silvio Lattanzi, Vahab S. Mirrokni:
A Local Algorithm for Finding Well-Connected Clusters. ICML (3) 2013: 396-404 - [c14]Lorenzo Alvisi, Allen Clement, Alessandro Epasto, Silvio Lattanzi, Alessandro Panconesi:
SoK: The Evolution of Sybil Defense via Social Networks. IEEE Symposium on Security and Privacy 2013: 382-396 - [c13]Shaomei Wu, Atish Das Sarma, Alex Fabrikant, Silvio Lattanzi, Andrew Tomkins:
Arrival and departure dynamics in social networks. WSDM 2013: 233-242 - 2011
- [c12]Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii, Andrea Vattani:
Hiring a secretary from a poset. EC 2011: 39-48 - [c11]Silvio Lattanzi, Benjamin Moseley, Siddharth Suri, Sergei Vassilvitskii:
Filtering: a method for solving graph problems in MapReduce. SPAA 2011: 85-94 - [c10]Ravi Kumar, Silvio Lattanzi, Prabhakar Raghavan:
An algorithmic treatment of strong queries. WSDM 2011: 775-784 - [c9]Silvio Lattanzi, Alessandro Panconesi, D. Sivakumar:
Milgram-routing in social networks. WWW 2011: 725-734 - 2010
- [c8]Flavio Chierichetti, Silvio Lattanzi, Alessandro Panconesi:
Rumour Spreading and Graph Conductance. SODA 2010: 1657-1663 - [c7]Flavio Chierichetti, Silvio Lattanzi, Alessandro Panconesi:
Almost tight bounds for rumour spreading with conductance. STOC 2010: 399-408 - 2009
- [c6]Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Alessandro Panconesi, Prabhakar Raghavan:
Models for the Compressible Web. FOCS 2009: 331-340 - [c5]Flavio Chierichetti, Silvio Lattanzi, Alessandro Panconesi:
Rumor Spreading in Social Networks. ICALP (2) 2009: 375-386 - [c4]Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Michael Mitzenmacher, Alessandro Panconesi, Prabhakar Raghavan:
On compressing social networks. KDD 2009: 219-228 - [c3]Silvio Lattanzi, D. Sivakumar:
Affiliation networks. STOC 2009: 427-434 - 2008
- [c2]Flavio Chierichetti, Silvio Lattanzi, Alessandro Panconesi:
Gossiping (via mobile?) in social networks. DIALM-POMC 2008: 27-28 - [c1]Flavio Chierichetti, Silvio Lattanzi, Federico Mari, Alessandro Panconesi:
On placing skips optimally in expectation. WSDM 2008: 15-24
Editorship
- 2024
- [e1]Luz Angelica Caudillo-Mata, Silvio Lattanzi, Andrés Muñoz Medina, Leman Akoglu, Aristides Gionis, Sergei Vassilvitskii:
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024. ACM 2024 [contents]
Informal and Other Publications
- 2024
- [i44]MohammadHossein Bateni, Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi:
A Scalable Algorithm for Individually Fair K-means Clustering. CoRR abs/2402.06730 (2024) - [i43]Paul Dütting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard, Morteza Zadimoghaddam:
Consistent Submodular Maximization. CoRR abs/2405.19977 (2024) - [i42]Vincent Cohen-Addad, Tommaso d'Orsi, Silvio Lattanzi, Rajai Nasser:
Multi-View Stochastic Block Models. CoRR abs/2406.04860 (2024) - [i41]Vincent Cohen-Addad, Silvio Lattanzi, Andreas Maggiori, Nikos Parotsidis:
Dynamic Correlation Clustering in Sublinear Update Time. CoRR abs/2406.09137 (2024) - [i40]Sayan Bhattacharya, Martín Costa, Naveen Garg, Silvio Lattanzi, Nikos Parotsidis:
Fully Dynamic k-Clustering with Fast Update Time and Small Recourse. CoRR abs/2408.01325 (2024) - 2023
- [i39]Paul Dütting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard, Morteza Zadimoghaddam:
Fully Dynamic Submodular Maximization over Matroids. CoRR abs/2305.19918 (2023) - [i38]Michael Dinitz, Satyen Kale, Silvio Lattanzi, Sergei Vassilvitskii:
Improved Differentially Private Densest Subgraph: Local and Purely Additive. CoRR abs/2308.10316 (2023) - [i37]Lorenzo Beretta, Vincent Cohen-Addad, Silvio Lattanzi, Nikos Parotsidis:
Multi-Swap k-Means++. CoRR abs/2309.16384 (2023) - [i36]Sayan Bhattacharya, Martín Costa, Silvio Lattanzi, Nikos Parotsidis:
Fully Dynamic k-Clustering in Õ(k) Update Time. CoRR abs/2310.17420 (2023) - [i35]Ainesh Bakshi, Vincent Cohen-Addad, Samuel B. Hopkins, Rajesh Jayaram, Silvio Lattanzi:
A quasi-polynomial time algorithm for Multi-Dimensional Scaling via LP hierarchies. CoRR abs/2311.17840 (2023) - 2022
- [i34]Paul Dütting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard, Morteza Zadimoghaddam:
Deletion Robust Submodular Maximization over Matroids. CoRR abs/2201.13128 (2022) - [i33]Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski:
Near-Optimal Correlation Clustering with Privacy. CoRR abs/2203.01440 (2022) - [i32]Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab S. Mirrokni, Andres Muñoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii:
Scalable Differentially Private Clustering via Hierarchically Separated Trees. CoRR abs/2206.08646 (2022) - [i31]Michael Kapralov, Akash Kumar, Silvio Lattanzi, Aida Mousavifar:
Learning Hierarchical Structure of Clusterable Graphs. CoRR abs/2207.02581 (2022) - [i30]Oleksandr Ferludin, Arno Eigenwillig, Martin Blais, Dustin Zelle, Jan Pfeifer, Alvaro Sanchez-Gonzalez, Wai Lok Sibon Li, Sami Abu-El-Haija, Peter W. Battaglia, Neslihan Bulut, Jonathan Halcrow, Filipe Miguel Gonçalves de Almeida, Silvio Lattanzi, André Linhares, Brandon A. Mayer, Vahab S. Mirrokni, John Palowitch, Mihir Paradkar, Jennifer She, Anton Tsitsulin, Kevin Villela, Lisa Wang, David Wong, Bryan Perozzi:
TF-GNN: Graph Neural Networks in TensorFlow. CoRR abs/2207.03522 (2022) - [i29]Paul Dütting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard, Morteza Zadimoghaddam:
Deletion Robust Non-Monotone Submodular Maximization over Matroids. CoRR abs/2208.07582 (2022) - [i28]Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice, Maximilian Thiessen:
Active Learning of Classifiers with Label and Seed Queries. CoRR abs/2209.03996 (2022) - [i27]Kimon Fountoulakis, Dake He, Silvio Lattanzi, Bryan Perozzi, Anton Tsitsulin, Shenghao Yang:
On Classification Thresholds for Graph Attention with Edge Features. CoRR abs/2210.10014 (2022) - [i26]Sayan Bhattacharya, Silvio Lattanzi, Nikos Parotsidis:
Efficient and Stable Fully Dynamic Facility Location. CoRR abs/2210.13880 (2022) - 2021
- [i25]Grzegorz Gluch, Michael Kapralov, Silvio Lattanzi, Aida Mousavifar, Christian Sohler:
Spectral Clustering Oracles in Sublinear Time. CoRR abs/2101.05549 (2021) - [i24]Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice:
Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries. CoRR abs/2102.00504 (2021) - [i23]Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice:
On Margin-Based Cluster Recovery with Oracle Queries. CoRR abs/2106.04913 (2021) - [i22]Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski:
Correlation Clustering in Constant Many Parallel Rounds. CoRR abs/2106.08448 (2021) - [i21]Michael Kapralov, Silvio Lattanzi, Navid Nouri, Jakab Tardos:
Efficient and Local Parallel Random Walks. CoRR abs/2112.00655 (2021) - 2020
- [i20]Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice:
Exact Recovery of Mangled Clusters with Same-Cluster Queries. CoRR abs/2006.04675 (2020) - [i19]Silvio Lattanzi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakub Tarnawski, Morteza Zadimoghaddam:
Fully Dynamic Algorithm for Constrained Submodular Optimization. CoRR abs/2006.04704 (2020) - [i18]Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Sliding Window Algorithms for k-Clustering Problems. CoRR abs/2006.05850 (2020) - [i17]Stefan Postavaru, Anton Tsitsulin, Filipe Miguel Gonçalves de Almeida, Yingtao Tian, Silvio Lattanzi, Bryan Perozzi:
InstantEmbedding: Efficient Local Node Representations. CoRR abs/2010.06992 (2020) - [i16]Luc Devroye, Silvio Lattanzi, Gábor Lugosi, Nikita Zhivotovskiy:
On Mean Estimation for Heteroscedastic Random Variables. CoRR abs/2010.11537 (2020) - [i15]Paul Dütting, Silvio Lattanzi, Renato Paes Leme, Sergei Vassilvitskii:
Secretaries with Advice. CoRR abs/2011.06726 (2020) - [i14]Hendrik Fichtenberger, Silvio Lattanzi, Ashkan Norouzi-Fard, Ola Svensson:
Consistent k-Clustering for General Metrics. CoRR abs/2011.06888 (2020) - [i13]Vincent Cohen-Addad, Silvio Lattanzi, Ashkan Norouzi-Fard, Christian Sohler, Ola Svensson:
Fast and Accurate k-means++ via Rejection Sampling. CoRR abs/2012.11891 (2020) - 2019
- [i12]Ehsan Kazemi, Marko Mitrovic, Morteza Zadimoghaddam, Silvio Lattanzi, Amin Karbasi:
Submodular Streaming in All its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity. CoRR abs/1905.00948 (2019) - [i11]MohammadTaghi Hajiaghayi, Silvio Lattanzi, Saeed Seddighin, Cliff Stein:
MapReduce Meets Fine-Grained Complexity: MapReduce Algorithms for APSP, Matrix Multiplication, 3-SUM, and Beyond. CoRR abs/1905.01748 (2019) - [i10]Giuseppe F. Italiano, Silvio Lattanzi, Vahab S. Mirrokni, Nikos Parotsidis:
Dynamic Algorithms for the Massively Parallel Computation Model. CoRR abs/1905.09175 (2019) - 2018
- [i9]Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii:
Fair Clustering Through Fairlets. CoRR abs/1802.05733 (2018) - [i8]Hossein Esfandiari, Silvio Lattanzi, Vahab S. Mirrokni:
Parallel and Streaming Algorithms for K-Core Decomposition. CoRR abs/1808.02546 (2018) - 2017
- [i7]Flavio Chierichetti, Sreenivas Gollapudi, Ravi Kumar, Silvio Lattanzi, Rina Panigrahy, David P. Woodruff:
Algorithms for $\ell_p$ Low Rank Approximation. CoRR abs/1705.06730 (2017) - [i6]Olivier Bachem, Mario Lucic, Silvio Lattanzi:
One-Shot Coresets: The Case of k-Clustering. CoRR abs/1711.09649 (2017) - [i5]Eduardo Fleury, Silvio Lattanzi, Vahab S. Mirrokni, Bryan Perozzi:
ASYMP: Fault-tolerant Mining of Massive Graphs. CoRR abs/1712.09731 (2017) - 2016
- [i4]Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Submodular Optimization over Sliding Windows. CoRR abs/1610.09984 (2016) - 2015
- [i3]Zeyuan Allen Zhu, Aditya Bhaskara, Silvio Lattanzi, Vahab S. Mirrokni, Lorenzo Orecchia:
Expanders via Local Edge Flips. CoRR abs/1510.07768 (2015) - 2013
- [i2]Zeyuan Allen Zhu, Silvio Lattanzi, Vahab S. Mirrokni:
A Local Algorithm for Finding Well-Connected Clusters. CoRR abs/1304.8132 (2013) - [i1]Nitish Korula, Silvio Lattanzi:
An efficient reconciliation algorithm for social networks. CoRR abs/1307.1690 (2013)
Coauthor Index
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