Gossiping (via mobile?) in social networks. - Flavio Chierichetti; Silvio Lattanzi; Alessandro Panconesi (DIALM-POMC, 2008)

On placing skips optimally in expectation. - Flavio Chierichetti; Silvio Lattanzi; Federico Mari; Alessandro Panconesi (WSDM, 2008)

On compressing social networks. - Flavio Chierichetti; Ravi Kumar 001; Silvio Lattanzi; Michael Mitzenmacher; Alessandro Panconesi; Prabhakar Raghavan (KDD, 2009)

Affiliation networks. - Silvio Lattanzi; D. Sivakumar 001 (STOC, 2009)

Rumour Spreading and Graph Conductance. - Flavio Chierichetti; Silvio Lattanzi; Alessandro Panconesi (SODA, 2010)

Almost tight bounds for rumour spreading with conductance. - Flavio Chierichetti; Silvio Lattanzi; Alessandro Panconesi (STOC, 2010)

Hiring a secretary from a poset. - Ravi Kumar 001; Silvio Lattanzi; Sergei Vassilvitskii; Andrea Vattani (EC, 2011)

Filtering: a method for solving graph problems in MapReduce. - Silvio Lattanzi; Benjamin Moseley; Siddharth Suri; Sergei Vassilvitskii (SPAA, 2011)

An algorithmic treatment of strong queries. - Ravi Kumar 001; Silvio Lattanzi; Prabhakar Raghavan (WSDM, 2011)

Milgram-routing in social networks. - Silvio Lattanzi; Alessandro Panconesi; D. Sivakumar 001 (WWW, 2011)

Rumor spreading in social networks. - Flavio Chierichetti; Silvio Lattanzi; Alessandro Panconesi (Theor. Comput. Sci., 2011)

A Local Algorithm for Finding Well-Connected Clusters. - Zeyuan Allen Zhu; Silvio Lattanzi; Vahab S. Mirrokni (ICML (3), 2013)

SoK: The Evolution of Sybil Defense via Social Networks. - Lorenzo Alvisi; Allen Clement; Alessandro Epasto; Silvio Lattanzi; Alessandro Panconesi (IEEE Symposium on Security and Privacy, 2013)

Arrival and departure dynamics in social networks. - Shaomei Wu; Atish Das Sarma; Alex Fabrikant; Silvio Lattanzi; Andrew Tomkins (WSDM, 2013)

Models for the Compressible Web. - Flavio Chierichetti; Ravi Kumar 001; Silvio Lattanzi; Alessandro Panconesi; Prabhakar Raghavan (SIAM J. Comput., 2013)

On Reconstructing a Hidden Permutation. - Flavio Chierichetti; Anirban Dasgupta 001; Ravi Kumar 001; Silvio Lattanzi (APPROX-RANDOM, 2014)

Connected Components in MapReduce and Beyond. - Raimondas Kiveris; Silvio Lattanzi; Vahab S. Mirrokni; Vibhor Rastogi; Sergei Vassilvitskii (SoCC, 2014)

Distributed Balanced Clustering via Mapping Coresets. - MohammadHossein Bateni; Aditya Bhaskara; Silvio Lattanzi; Vahab S. Mirrokni (NIPS, 2014)

Filter & follow: how social media foster content curation. - Avner May; Augustin Chaintreau; Nitish Korula; Silvio Lattanzi (SIGMETRICS, 2014)

Learning Entangled Single-Sample Gaussians. - Flavio Chierichetti; Anirban Dasgupta 001; Ravi Kumar 001; Silvio Lattanzi (SODA, 2014)

Reduce and aggregate: similarity ranking in multi-categorical bipartite graphs. - Alessandro Epasto; Jon Feldman; Silvio Lattanzi; Stefano Leonardi 001; Vahab S. Mirrokni (WWW, 2014)

Communities, Random Walks, and Social Sybil Defense. - Lorenzo Alvisi; Allen Clement; Alessandro Epasto; Silvio Lattanzi; Alessandro Panconesi (Internet Math., 2014)

An efficient reconciliation algorithm for social networks. - Nitish Korula; Silvio Lattanzi (Proc. VLDB Endow., 2014)

On Learning Mixture Models for Permutations. - Flavio Chierichetti; Anirban Dasgupta 001; Ravi Kumar 001; Silvio Lattanzi (ITCS, 2015)

Robust Hierarchical k-Center Clustering. - Silvio Lattanzi; Stefano Leonardi 001; Vahab S. Mirrokni; Ilya P. Razenshteyn (ITCS, 2015)

Efficient Algorithms for Public-Private Social Networks. - Flavio Chierichetti; Alessandro Epasto; Ravi Kumar 001; Silvio Lattanzi; Vahab S. Mirrokni (KDD, 2015)

Distributed Graph Algorithmics: Theory and Practice. - Silvio Lattanzi; Vahab S. Mirrokni (WSDM, 2015)

The Power of Random Neighbors in Social Networks. - Silvio Lattanzi; Yaron Singer (WSDM, 2015)

Efficient Densest Subgraph Computation in Evolving Graphs. - Alessandro Epasto; Silvio Lattanzi; Mauro Sozio (WWW, 2015)

Ego-net Community Mining Applied to Friend Suggestion. - Alessandro Epasto; Silvio Lattanzi; Vahab S. Mirrokni; Ismail Sebe; Ahmed Taei; Sunita Verma (Proc. VLDB Endow., 2015)

Community Detection on Evolving Graphs. - Aris Anagnostopoulos; Jakub Lacki; Silvio Lattanzi; Stefano Leonardi 001; Mohammad Mahdian (NIPS, 2016)

Expanders via Local Edge Flips. - Zeyuan Allen Zhu; Aditya Bhaskara; Silvio Lattanzi; Vahab S. Mirrokni; Lorenzo Orecchia (SODA, 2016)

On Sampling Nodes in a Network. - Flavio Chierichetti; Anirban Dasgupta 001; Ravi Kumar 001; Silvio Lattanzi; Tamás Sarlós (WWW, 2016)

Linking Users Across Domains with Location Data: Theory and Validation. - Christopher J. Riederer; Yunsung Kim; Augustin Chaintreau; Nitish Korula; Silvio Lattanzi (WWW, 2016)

Efficient computation of the Weighted Clustering Coefficient. - Silvio Lattanzi; Stefano Leonardi 001 (Internet Math., 2016)

Algorithms for $ ell_p$ Low-Rank Approximation. - Flavio Chierichetti; Sreenivas Gollapudi; Ravi Kumar 001; Silvio Lattanzi; Rina Panigrahy; David P. Woodruff (ICML, 2017)

Consistent k-Clustering. - Silvio Lattanzi; Sergei Vassilvitskii (ICML, 2017)

Ego-Splitting Framework: from Non-Overlapping to Overlapping Clusters. - Alessandro Epasto; Silvio Lattanzi; Renato Paes Leme (KDD, 2017)

Affinity Clustering: Hierarchical Clustering at Scale. - MohammadHossein Bateni; Soheil Behnezhad; Mahsa Derakhshan; MohammadTaghi Hajiaghayi; Raimondas Kiveris; Silvio Lattanzi; Vahab S. Mirrokni (NIPS, 2017)

Fair Clustering Through Fairlets. - Flavio Chierichetti; Ravi Kumar 001; Silvio Lattanzi; Sergei Vassilvitskii (NIPS, 2017)

Indexing Public-Private Graphs. - Aaron Archer; Silvio Lattanzi; Peter Likarish; Sergei Vassilvitskii (WWW, 2017)

Submodular Optimization Over Sliding Windows. - Alessandro Epasto; Silvio Lattanzi; Sergei Vassilvitskii; Morteza Zadimoghaddam (WWW, 2017)

ASYMP: Fault-tolerant Mining of Massive Graphs. - Eduardo Fleury; Silvio Lattanzi; Vahab S. Mirrokni; Bryan Perozzi (CoRR, 2017)

One-shot Coresets: The Case of k-Clustering. - Olivier Bachem; Mario Lucic; Silvio Lattanzi (AISTATS, 2018)

Parallel and Streaming Algorithms for K-Core Decomposition. - Hossein Esfandiari; Silvio Lattanzi; Vahab S. Mirrokni (ICML, 2018)

Non-Negative Sparse Regression and Column Subset Selection with L1 Error. - Aditya Bhaskara; Silvio Lattanzi (ITCS, 2018)

Mallows Models for Top-k Lists. - Flavio Chierichetti; Anirban Dasgupta 001; Shahrzad Haddadan; Ravi Kumar 001; Silvio Lattanzi (NeurIPS, 2018)

Rumor Spreading and Conductance. - Flavio Chierichetti; George Giakkoupis; Silvio Lattanzi; Alessandro Panconesi (J. ACM, 2018)

Matroids, Matchings, and Fairness. - Flavio Chierichetti; Ravi Kumar 001; Silvio Lattanzi; Sergei Vassilvitskii (AISTATS, 2019)

Consistent Online Optimization: Convex and Submodular. - Mohammad Reza Karimi Jaghargh; Andreas Krause 001; Silvio Lattanzi; Sergei Vassilvitskii (AISTATS, 2019)

Residual Based Sampling for Online Low Rank Approximation. - Aditya Bhaskara; Silvio Lattanzi; Sergei Vassilvitskii; Morteza Zadimoghaddam (FOCS, 2019)

Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity. - Ehsan Kazemi 001; Marko Mitrovic; Morteza Zadimoghaddam; Silvio Lattanzi; Amin Karbasi (ICML, 2019)

Improved Parallel Algorithms for Density-Based Network Clustering. - Mohsen Ghaffari 001; Silvio Lattanzi; Slobodan Mitrovic (ICML, 2019)

A Better k-means++ Algorithm via Local Search. - Silvio Lattanzi; Christian Sohler (ICML, 2019)

A Framework for Parallelizing Hierarchical Clustering Methods. - Silvio Lattanzi; Thomas Lavastida; Kefu Lu; Benjamin Moseley (ECML/PKDD (1), 2019)

Better Sliding Window Algorithms to Maximize Subadditive and Diversity Objectives. - Michele Borassi; Alessandro Epasto; Silvio Lattanzi; Sergei Vassilvitskii; Morteza Zadimoghaddam (PODS, 2019)

Dynamic Algorithms for the Massively Parallel Computation Model. - Giuseppe F. Italiano; Silvio Lattanzi; Vahab S. Mirrokni; Nikos Parotsidis (SPAA, 2019)

MapReduce Meets Fine-Grained Complexity: MapReduce Algorithms for APSP, Matrix Multiplication, 3-SUM, and Beyond. - MohammadTaghi Hajiaghayi; Silvio Lattanzi; Saeed Seddighin; Cliff Stein 001 (CoRR, 2019)

Introduction to the Special Issue for SPAA'17. - Mohammad Hossein Bateni 001; Mohammad Taghi Hajiaghayi; Silvio Lattanzi (ACM Trans. Parallel Comput., 2019)

Exact Recovery of Mangled Clusters with Same-Cluster Queries. - Marco Bressan 002; Nicolò Cesa-Bianchi; Silvio Lattanzi; Andrea Paudice (NeurIPS, 2020)

Online MAP Inference of Determinantal Point Processes. - Aditya Bhaskara; Amin Karbasi; Silvio Lattanzi; Morteza Zadimoghaddam (NeurIPS, 2020)

Sliding Window Algorithms for k-Clustering Problems. - Michele Borassi; Alessandro Epasto; Silvio Lattanzi; Sergei Vassilvitskii; Morteza Zadimoghaddam (NeurIPS, 2020)

Fast and Accurate $k$-means++ via Rejection Sampling. - Vincent Cohen-Addad; Silvio Lattanzi; Ashkan Norouzi-Fard; Christian Sohler; Ola Svensson (NeurIPS, 2020)

Fully Dynamic Algorithm for Constrained Submodular Optimization. - Silvio Lattanzi; Slobodan Mitrovic; Ashkan Norouzi-Fard; Jakub Tarnawski; Morteza Zadimoghaddam (NeurIPS, 2020)

Online Scheduling via Learned Weights. - Silvio Lattanzi; Thomas Lavastida; Benjamin Moseley; Sergei Vassilvitskii (SODA, 2020)

InstantEmbedding: Efficient Local Node Representations. - Stefan Postavaru; Anton Tsitsulin; Filipe Miguel Gonçalves de Almeida; Yingtao Tian; Silvio Lattanzi; Bryan Perozzi (CoRR, 2020)

On Mean Estimation for Heteroscedastic Random Variables. - Luc Devroye; Silvio Lattanzi; Gábor Lugosi; Nikita Zhivotovskiy (CoRR, 2020)

Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries. - Marco Bressan 002; Nicolò Cesa-Bianchi; Silvio Lattanzi; Andrea Paudice (COLT, 2021)

Correlation Clustering in Constant Many Parallel Rounds. - Vincent Cohen-Addad; Silvio Lattanzi; Slobodan Mitrovic; Ashkan Norouzi-Fard; Nikos Parotsidis; Jakub Tarnawski (ICML, 2021)

Online Facility Location with Multiple Advice. - Matteo Almanza; Flavio Chierichetti; Silvio Lattanzi; Alessandro Panconesi; Giuseppe Re (NeurIPS, 2021)

On Margin-Based Cluster Recovery with Oracle Queries. - Marco Bressan 002; Nicolò Cesa-Bianchi; Silvio Lattanzi; Andrea Paudice (NeurIPS, 2021)

Parallel and Efficient Hierarchical k-Median Clustering. - Vincent Cohen-Addad; Silvio Lattanzi; Ashkan Norouzi-Fard; Christian Sohler; Ola Svensson (NeurIPS, 2021)

Efficient and Local Parallel Random Walks. - Michael Kapralov; Silvio Lattanzi; Navid Nouri; Jakab Tardos (NeurIPS, 2021)

Robust Online Correlation Clustering. - Silvio Lattanzi; Benjamin Moseley; Sergei Vassilvitskii; Yuyan Wang; Rudy Zhou (NeurIPS, 2021)

Consistent k-Clustering for General Metrics. - Hendrik Fichtenberger; Silvio Lattanzi; Ashkan Norouzi-Fard; Ola Svensson (SODA, 2021)

Spectral Clustering Oracles in Sublinear Time. - Grzegorz Gluch; Michael Kapralov; Silvio Lattanzi; Aida Mousavifar; Christian Sohler (SODA, 2021)

Twin Peaks, a Model for Recurring Cascades. - Matteo Almanza; Silvio Lattanzi; Alessandro Panconesi; Giuseppe Re (WWW, 2021)

Approximate Cluster Recovery from Noisy Labels. - Buddhima Gamlath; Silvio Lattanzi; Ashkan Norouzi-Fard; Ola Svensson (COLT, 2022)

Online and Consistent Correlation Clustering. - Vincent Cohen-Addad; Silvio Lattanzi; Andreas Maggiori; Nikos Parotsidis (ICML, 2022)

Deletion Robust Submodular Maximization over Matroids. - Paul Duetting; Federico Fusco; Silvio Lattanzi; Ashkan Norouzi-Fard; Morteza Zadimoghaddam (ICML, 2022)

Scalable Differentially Private Clustering via Hierarchically Separated Trees. - Vincent Cohen-Addad; Alessandro Epasto; Silvio Lattanzi; Vahab Mirrokni; Andres Muñoz Medina; David Saulpic; Chris Schwiegelshohn; Sergei Vassilvitskii (KDD, 2022)

Active Learning of Classifiers with Label and Seed Queries. - Marco Bressan 002; Nicolò Cesa-Bianchi; Silvio Lattanzi; Andrea Paudice; Maximilian Thiessen (NeurIPS, 2022)

Efficient and Stable Fully Dynamic Facility Location. - Sayan Bhattacharya; Silvio Lattanzi; Nikos Parotsidis (NeurIPS, 2022)

Near-Optimal Correlation Clustering with Privacy. - Vincent Cohen-Addad; Chenglin Fan; Silvio Lattanzi; Slobodan Mitrovic; Ashkan Norouzi-Fard; Nikos Parotsidis; Jakub Tarnawski (NeurIPS, 2022)

The Gibbs-Rand Model. - Flavio Chierichetti; Ravi Kumar 001; Silvio Lattanzi (PODS, 2022)

Learning Hierarchical Structure of Clusterable Graphs. - Michael Kapralov; Akash Kumar 009; Silvio Lattanzi; Aida Mousavifar (CoRR, 2022)

TF-GNN: Graph Neural Networks in TensorFlow. - 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; et al. (CoRR, 2022)

Deletion Robust Non-Monotone Submodular Maximization over Matroids. - Paul Dütting; Federico Fusco; Silvio Lattanzi; Ashkan Norouzi-Fard; Morteza Zadimoghaddam (CoRR, 2022)

On Classification Thresholds for Graph Attention with Edge Features. - Kimon Fountoulakis; Dake He; Silvio Lattanzi; Bryan Perozzi; Anton Tsitsulin; Shenghao Yang 002 (CoRR, 2022)

Speeding Up Bellman Ford via Minimum Violation Permutations. - Silvio Lattanzi; Ola Svensson; Sergei Vassilvitskii (ICML, 2023)

Multi-Swap k-Means++. - Lorenzo Beretta 001; Vincent Cohen-Addad; Silvio Lattanzi; Nikos Parotsidis (NeurIPS, 2023)

Fully Dynamic k-Clustering in Õ(k) Update Time. - Sayan Bhattacharya; Martín Costa; Silvio Lattanzi; Nikos Parotsidis (NeurIPS, 2023)

Learning Hierarchical Cluster Structure of Graphs in Sublinear Time. - Michael Kapralov; Akash Kumar 009; Silvio Lattanzi; Aida Mousavifar (SODA, 2023)

Improved Differentially Private Densest Subgraph: Local and Purely Additive. - Michael Dinitz; Satyen Kale; Silvio Lattanzi; Sergei Vassilvitskii (CoRR, 2023)

A quasi-polynomial time algorithm for Multi-Dimensional Scaling via LP hierarchies. - Ainesh Bakshi; Vincent Cohen-Addad; Samuel B. Hopkins 001; Rajesh Jayaram; Silvio Lattanzi (CoRR, 2023)

Massively Parallel Computation: Algorithms and Applications. - Sungjin Im; Ravi Kumar 001; Silvio Lattanzi; Benjamin Moseley; Sergei Vassilvitskii (Found. Trends Optim., 2023)

A Scalable Algorithm for Individually Fair k-Means Clustering. - MohammadHossein Bateni; Vincent Cohen-Addad; Alessandro Epasto; Silvio Lattanzi (AISTATS, 2024)

Fully Dynamic k-Clustering with Fast Update Time and Small Recourse. - Sayan Bhattacharya; Martín Costa; Naveen Garg; Silvio Lattanzi; Nikos Parotsidis (FOCS, 2024)

Dynamic Correlation Clustering in Sublinear Update Time. - Vincent Cohen-Addad; Silvio Lattanzi; Andreas Maggiori; Nikos Parotsidis (ICML, 2024)

Multi-View Stochastic Block Models. - Vincent Cohen-Addad; Tommaso d'Orsi; Silvio Lattanzi; Rajai Nasser (ICML, 2024)

Consistent Submodular Maximization. - Paul Duetting; Federico Fusco; Silvio Lattanzi; Ashkan Norouzi-Fard; Morteza Zadimoghaddam (ICML, 2024)

Resilient k-Clustering. - Sara Ahmadian; MohammadHossein Bateni; Hossein Esfandiari; Silvio Lattanzi; Morteza Monemizadeh; Ashkan Norouzi-Fard (KDD, 2024)

Fully Dynamic k-Clustering with Fast Update Time and Small Recourse. - Sayan Bhattacharya; Martín Costa; Naveen Garg; Silvio Lattanzi; Nikos Parotsidis (CoRR, 2024)

Fully Dynamic k-Center Clustering Made Simple. - Sayan Bhattacharya; Martín Costa; Silvio Lattanzi; Nikos Parotsidis (CoRR, 2024)

Margin-Based Active Learning of Classifiers. - Marco Bressan 002; Nicolò Cesa-Bianchi; Silvio Lattanzi; Andrea Paudice (J. Mach. Learn. Res., 2024)

Secretaries with Advice. - Paul Dütting; Silvio Lattanzi; Renato Paes Leme; Sergei Vassilvitskii (Math. Oper. Res., 2024)

Fully Dynamic k-Center Clustering with Outliers. - T.-H. Hubert Chan; Silvio Lattanzi; Mauro Sozio; Bo Wang 156 (Algorithmica, 2024)

Metric Embeddings Beyond Bi-Lipschitz Distortion via Sherali-Adams. - Ainesh Bakshi; Vincent Cohen-Addad; Rajesh Jayaram; Sam Hopkins 001; Silvio Lattanzi (COLT, 2025)

Approximating Dasgupta Cost in Sublinear Time from a Few Random Seeds. - Michael Kapralov; Akash Kumar 009; Silvio Lattanzi; Aida Mousavifar; Weronika Wrzos-Kaminska (ICALP, 2025)

Data-Driven Solution Portfolios. - Marina Drygala; Silvio Lattanzi; Andreas Maggiori; Miltiadis Stouras; Ola Svensson; Sergei Vassilvitskii (ITCS, 2025)

Almost Tight Bounds for Differentially Private Densest Subgraph. - Michael Dinitz; Satyen Kale; Silvio Lattanzi; Sergei Vassilvitskii (SODA, 2025)

Almost Optimal PAC Learning for k-Means. - Vincent Cohen-Addad; Silvio Lattanzi; Chris Schwiegelshohn (STOC, 2025)

The Cost of Consistency: Submodular Maximization with Constant Recourse. - Paul Dütting; Federico Fusco; Silvio Lattanzi; Ashkan Norouzi-Fard; Ola Svensson; Morteza Zadimoghaddam (STOC, 2025)

Fully Dynamic Submodular Maximization over Matroids. - Paul Dütting; Federico Fusco; Silvio Lattanzi; Ashkan Norouzi-Fard; Morteza Zadimoghaddam (ACM Trans. Algorithms, 2025)

Large-Scale Graph Building in Dynamic Environments: Low Latency and High Quality. - Filipe Miguel Gonçalves de Almeida; CJ Carey; Hendrik Fichtenberger; Jonathan Halcrow; Silvio Lattanzi; André Linhares; Tao Meng; Ashkan Norouzi-Fard; Nikos Parotsidis; Bryan Perozzi; David Simcha (CoRR, 2025)