Two Improved Range-Efficient Algorithms for F 0 Estimation. - He Sun 001; Chung Keung Poon (TAMC, 2007)

A Fast 2-Approximation Algorithm for the Minimum Manhattan Network Problem. - Zeyu Guo 001; He Sun 001; Hong Zhu 004 (AAIM, 2008)

Greedy Construction of 2-Approximation Minimum Manhattan Network. - Zeyu Guo 001; He Sun 001; Hong Zhu 004 (ISAAC, 2008)

On Construction of Almost-Ramanujan Graphs. - He Sun 001; Hong Zhu 004 (Discret. Math. Algorithms Appl., 2009)

Two improved range-efficient algorithms for F0 estimation. - He Sun 001; Chung Keung Poon (Theor. Comput. Sci., 2009)

Approximate Counting of Cycles in Streams. - Madhusudan Manjunath; Kurt Mehlhorn; Konstantinos Panagiotou; He Sun 001 (ESA, 2011)

Minimum Manhattan Network is NP-Complete. - Francis Y. L. Chin; Zeyu Guo 001; He Sun 001 (Discret. Comput. Geom., 2011)

Greedy Construction of 2-Approximate Minimum Manhattan Networks. - Zeyu Guo 001; He Sun 001; Hong Zhu 004 (Int. J. Comput. Geom. Appl., 2011)

Tight Bounds for Randomized Load Balancing on Arbitrary Network Topologies. - Thomas Sauerwald; He Sun 001 (FOCS, 2012)

Counting Arbitrary Subgraphs in Data Streams. - Daniel M. Kane; Kurt Mehlhorn; Thomas Sauerwald; He Sun 001 (ICALP (2), 2012)

Low Randomness Rumor Spreading via Hashing. - George Giakkoupis; Thomas Sauerwald; He Sun 001; Philipp Woelfel (STACS, 2012)

Multi-Attribute Profit-Maximizing Pricing (Extended Abstract) - Parinya Chalermsook; Khaled M. Elbassioni; Danupon Nanongkai; He Sun 001 (CoRR, 2012)

Balls into Bins via Local Search. - Paul Bogdan; Thomas Sauerwald; Alexandre Stauffer; He Sun 001 (SODA, 2013)

Counting Hypergraphs in Data Streams - He Sun 001 (CoRR, 2013)

Deterministic polynomial-time algorithms for designing short DNA words. - Ming-Yang Kao; Henry C. M. Leung; He Sun 001; Yong Zhang 001 (Theor. Comput. Sci., 2013)

Dirichlet Eigenvalues, Local Random Walks, and Analyzing Clusters in Graphs. - Pavel Kolev; He Sun 001 (ISAAC, 2014)

Partitioning Well-Clustered Graphs with k-Means and Heat Kernel. - Richard Peng; He Sun 001; Luca Zanetti (CoRR, 2014)

Gossip vs. Markov Chains, and Randomness-Efficient Rumor Spreading. - Zeyu Guo 001; He Sun 001 (SODA, 2015)

Randomized Rumour Spreading: The Effect of the Network Topology. - Konstantinos Panagiotou; Xavier Pérez-Giménez; Thomas Sauerwald; He Sun 001 (Comb. Probab. Comput., 2015)

Communication-Optimal Distributed Clustering. - Jiecao Chen; He Sun 001; David P. Woodruff; Qin Zhang 001 (NIPS, 2016)

Balls into bins via local search: Cover time and maximum load. - Karl Bringmann; Thomas Sauerwald; Alexandre Stauffer; He Sun 001 (Random Struct. Algorithms, 2016)

Distributed Graph Clustering by Load Balancing. - He Sun 001; Luca Zanetti (SPAA, 2017)

An SDP-based algorithm for linear-sized spectral sparsification. - Yin Tat Lee; He Sun 001 (STOC, 2017)

Partitioning Well-Clustered Graphs: Spectral Clustering Works! - Richard Peng; He Sun 001; Luca Zanetti (SIAM J. Comput., 2017)

Constructing Linear-Sized Spectral Sparsification in Almost-Linear Time. - Yin Tat Lee; He Sun 001 (SIAM J. Comput., 2018)

Hermitian Laplacians and a Cheeger Inequality for the Max-2-Lin Problem. - Huan Li 002; He Sun 001; Luca Zanetti (ESA, 2019)

Distributed Graph Clustering and Sparsification. - He Sun 001; Luca Zanetti (ACM Trans. Parallel Comput., 2019)

Hermitian matrices for clustering directed graphs: insights and applications. - Mihai Cucuringu; Huan Li 002; He Sun 001; Luca Zanetti (AISTATS, 2020)

Augmenting the Algebraic Connectivity of Graphs. - Bogdan-Adrian Manghiuc; Pan Peng 001; He Sun 001 (ESA, 2020)

Higher-Order Spectral Clustering of Directed Graphs. - Steinar Laenen; He Sun 001 (NeurIPS, 2020)

Local Algorithms for Finding Densely Connected Clusters. - Peter Macgregor; He Sun 001 (ICML, 2021)

Finding Bipartite Components in Hypergraphs. - Peter Macgregor; He Sun 001 (NeurIPS, 2021)

Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs. - Bogdan-Adrian Manghiuc; He Sun 001 (NeurIPS, 2021)

Fully-Dynamic Graph Sparsifiers Against an Adaptive Adversary. - Aaron Bernstein; Jan van den Brand; Maximilian Probst Gutenberg; Danupon Nanongkai; Thatchaphol Saranurak; Aaron Sidford; He Sun 001 (ICALP, 2022)

A Tighter Analysis of Spectral Clustering, and Beyond. - Peter Macgregor; He Sun 001 (ICML, 2022)

The Support of Open Versus Closed Random Walks. - Thomas Sauerwald; He Sun 001; Danny Vagnozzi (ICALP, 2023)

Nearly-Optimal Hierarchical Clustering for Well-Clustered Graphs. - Steinar Laenen; Bogdan-Adrian Manghiuc; He Sun 001 (ICML, 2023)

Is the Algorithmic Kadison-Singer Problem Hard? - Ben Jourdan; Peter Macgregor; He Sun 001 (ISAAC, 2023)

Fast Approximation of Similarity Graphs with Kernel Density Estimation. - Peter Macgregor; He Sun 001 (NeurIPS, 2023)

Spectral Toolkit of Algorithms for Graphs: Technical Report (1). - Peter Macgregor; He Sun 001 (CoRR, 2023)

Three Hardness Results for Graph Similarity Problems. - He Sun 001; Danny Vagnozzi (CoRR, 2023)

Dynamic Spectral Clustering with Provable Approximation Guarantee. - Steinar Laenen; He Sun 001 (ICML, 2024)

Polynomial-Time Algorithms for Weaver's Discrepancy Problem in a Dense Regime. - Ben Jourdan; Peter Macgregor; He Sun 001 (CoRR, 2024)

Spectral Toolkit of Algorithms for Graphs: Technical Report (2). - Peter Macgregor; He Sun 001 (CoRR, 2024)

Coreset Spectral Clustering. - Ben Jourdan; Gregory Schwartzman; Peter Macgregor; He Sun 001 (ICLR, 2025)

Can We Measure the Impact of a Database? - Peter Buneman; Dennis Dosso; Matteo Lissandrini; Gianmaria Silvello; He Sun 001 (Commun. ACM, 2025)

Dynamic Similarity Graph Construction with Kernel Density Estimation. - Steinar Laenen; Peter Macgregor; He Sun 001 (CoRR, 2025)