Quanquan C. Liu

67 papers A* 4A 13B 8Misc 1Journal 37Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic Evolution. CoRR Liu Yang, Zeyu Nie, Andrew Liu, Felix Zou, Deniz Altinbüken, Amir Yazdanbakhsh, Quanquan C. Liu
2026	J	`jnl`	QEDBENCH: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs. CoRR Santiago Gonzalez, Alireza Amiri Bavandpour, Peter Ye, Edward Zhang, Ruslans Aleksejevs, Todor Antic, Polina Baron, Sujeet Bhalerao, Shubhrajit Bhattacharya, Zachary Burton, John Byrne, Hyungjun Choi, Nujhat Ahmed Disha, Koppány István Encz, Yuchen Fang, Robert Joseph George, Ebrahim Ghorbani, Alan Goldfarb, Jing Guo, Meghal Gupta, Stefano Huber, Annika Kanckos, Minjung Kang, Hyun Jong Kim, Dino Lorenzini, Levi Lorenzo, Tianyi Mao, Giovanni Marzenta, Ariane M. Masuda, Lukas Mauth, Ana Mickovic, Andres Miniguano-Trujillo, Antoine Moulin, Wenqi Ni, Tomos Parry, Kevin Ren, Hossein Roodbarani, Mathieu Rundström, Manjil Saikia, Detchat Samart, Rebecca Steiner, Connor Stewart, Dhara Thakkar, Jeffrey Tse, Vasiliki Velona, Yunhai Xiang, Sibel Yalçin, Jun Yan, Ji Zeng, Arman Cohan, Quanquan C. Liu
2025	B	`conf`	Dataflow-Specific Algorithms for Resource-Constrained Scheduling and Memory Design. SPAA Abhishek Bhattacharjee, Quanquan C. Liu, Rajit Manohar, Raghavendra Pradyumna Pothukuchi, Muhammed Ugur
2025	J	`jnl`	Differentially Private Matchings. CoRR Michael Dinitz, George Z. Li, Quanquan C. Liu, Felix Zhou
2025	A	`conf`	Near-Optimal Differentially Private Graph Algorithms via the Multidimensional AboveThreshold Mechanism. ESA Laxman Dhulipala, Monika Henzinger, George Z. Li, Quanquan C. Liu, A. R. Sricharan, Leqi Zhu
2025	J	`jnl`	Near-Optimal Differentially Private Graph Algorithms via the Multidimensional AboveThreshold Mechanism. CoRR Laxman Dhulipala, Monika Henzinger, George Z. Li, Quanquan C. Liu, A. R. Sricharan, Leqi Zhu
2025	J	`jnl`	Practical and Accurate Local Edge Differentially Private Graph Algorithms. CoRR Pranay Mundra, Charalampos Papamanthou, Julian Shun, Quanquan C. Liu
2025	J	`jnl`	Practical and Accurate Local Edge Differentially Private Graph Algorithms. Proc. VLDB Endow. Pranay Mundra, Charalampos Papamanthou, Julian Shun, Quanquan C. Liu
2025	A	`conf`	Sublinear Space Graph Algorithms in the Continual Release Model. APPROX/RANDOM Alessandro Epasto, Quanquan C. Liu, Tamalika Mukherjee, Felix Zhou
2025	J	`jnl`	Triangle Counting With Local Edge Differential Privacy. Random Struct. Algorithms Talya Eden, Quanquan C. Liu, Sofya Raskhodnikova, Adam D. Smith
2024	A*	`conf`	Brief Announcement: Improved Massively Parallel Triangle Counting in O(1) Rounds. PODC Quanquan C. Liu, C. Seshadhri
2024	A	`conf`	Fair Allocation of Conflicting Courses under Additive Utilities. AAMAS Arpita Biswas, Yiduo Ke, Samir Khuller, Quanquan C. Liu
2024	J	`jnl`	Improved Massively Parallel Triangle Counting in O(1) Rounds. CoRR Quanquan C. Liu, C. Seshadhri
2024	B	`conf`	Parallel k-Core Decomposition with Batched Updates and Asynchronous Reads. PPoPP Quanquan C. Liu, Julian Shun, Igor Zablotchi
2024	J	`jnl`	Parallel k-Core Decomposition with Batched Updates and Asynchronous Reads. CoRR Quanquan C. Liu, Julian Shun, Igor Zablotchi
2024	J	`jnl`	Pointwise Lipschitz Continuous Graph Algorithms via Proximal Gradient Analysis. CoRR Quanquan C. Liu, Grigoris Velegkas, Yuichi Yoshida, Felix Zhou
2024	A	`conf`	Practical Parallel Algorithms for Near-Optimal Densest Subgraphs on Massive Graphs. ALENEX Pattara Sukprasert, Quanquan C. Liu, Laxman Dhulipala, Julian Shun
2024	J	`jnl`	The Power of Graph Sparsification in the Continual Release Model. CoRR Alessandro Epasto, Quanquan C. Liu, Tamalika Mukherjee, Felix Zhou
2024	A*	`conf`	The Predicted-Updates Dynamic Model: Offline, Incremental, and Decremental to Fully Dynamic Transformations. COLT Quanquan C. Liu, Vaidehi Srinivas
2023	J	`jnl`	A note on improved results for one round distributed clique listing. Inf. Process. Lett. Quanquan C. Liu
2023	—	`conf`	An Algorithmic Approach to Address Course Enrollment Challenges. FORC Arpita Biswas, Yiduo Ke, Samir Khuller, Quanquan C. Liu
2023	J	`jnl`	An Algorithmic Approach to Address Course Enrollment Challenges. CoRR Arpita Biswas, Yiduo Ke, Samir Khuller, Quanquan C. Liu
2023	J	`jnl`	Near-Optimal Differentially Private k-Core Decomposition. CoRR Laxman Dhulipala, George Z. Li, Quanquan C. Liu
2023	J	`jnl`	Practical Parallel Algorithms for Near-Optimal Densest Subgraphs on Massive Graphs. CoRR Pattara Sukprasert, Quanquan C. Liu, Laxman Dhulipala, Julian Shun
2023	A	`conf`	Scalable Auction Algorithms for Bipartite Maximum Matching Problems. APPROX/RANDOM Quanquan C. Liu, Yiduo Ke, Samir Khuller
2023	J	`jnl`	Scalable Auction Algorithms for Bipartite Maximum Matching Problems. CoRR Quanquan C. Liu, Yiduo Ke, Samir Khuller
2023	J	`jnl`	The Predicted-Deletion Dynamic Model: Taking Advantage of ML Predictions, for Free. CoRR Quanquan C. Liu, Vaidehi Srinivas
2023	A*	`conf`	Triangle Counting with Local Edge Differential Privacy. ICALP Talya Eden, Quanquan C. Liu, Sofya Raskhodnikova, Adam Smith
2023	J	`jnl`	Triangle Counting with Local Edge Differential Privacy. CoRR Talya Eden, Quanquan C. Liu, Sofya Raskhodnikova, Adam D. Smith
2022	J	`jnl`	A Note on Improved Results for One Round Distributed Clique Listing. CoRR Quanquan C. Liu
2022	A*	`conf`	Differential Privacy from Locally Adjustable Graph Algorithms: k-Core Decomposition, Low Out-Degree Ordering, and Densest Subgraphs. FOCS Laxman Dhulipala, Quanquan C. Liu, Sofya Raskhodnikova, Jessica Shi, Julian Shun, Shangdi Yu
2022	J	`jnl`	Differential Privacy from Locally Adjustable Graph Algorithms: k-Core Decomposition, Low Out-Degree Ordering, and Densest Subgraphs. CoRR Laxman Dhulipala, Quanquan C. Liu, Sofya Raskhodnikova, Jessica Shi, Julian Shun, Shangdi Yu
2022	J	`jnl`	Fully Dynamic (Δ +1)-Coloring in ACM Trans. Algorithms Sayan Bhattacharya, Fabrizio Grandoni, Janardhan Kulkarni, Quanquan C. Liu, Shay Solomon
2022	A	`conf`	Massively Parallel Algorithms for Small Subgraph Counting. APPROX/RANDOM Amartya Shankha Biswas, Talya Eden, Quanquan C. Liu, Ronitt Rubinfeld, Slobodan Mitrovic
2022	A	`conf`	Near-Optimal Distributed Implementations of Dynamic Algorithms for Symmetry Breaking Problems. ITCS Shiri Antaki, Quanquan C. Liu, Shay Solomon
2022	B	`conf`	Parallel Batch-Dynamic Algorithms for k-Core Decomposition and Related Graph Problems. SPAA Quanquan C. Liu, Jessica Shi, Shangdi Yu, Laxman Dhulipala, Julian Shun
2022	A	`conf`	Scheduling with Communication Delay in Near-Linear Time. STACS Quanquan C. Liu, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang
2021	—	`conf`	Parallel Batch-Dynamic APOCS Laxman Dhulipala, Quanquan C. Liu, Julian Shun, Shangdi Yu
2021	J	`jnl`	Parallel Batch-Dynamic k-Core Decomposition. CoRR Quanquan C. Liu, Jessica Shi, Shangdi Yu, Laxman Dhulipala, Julian Shun
2021	—	`—`	Scalable and Efficient Graph Algorithms and Analysis Techniques for Modern Machines. Quanquan C. Liu
2021	J	`jnl`	Scheduling with Communication Delay in Near-Linear Time. CoRR Quanquan C. Liu, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang
2021	Misc	`conf`	Tatamibari Is NP-Complete. FUN Aviv Adler, Jeffrey Bosboom, Erik D. Demaine, Martin L. Demaine, Quanquan C. Liu, Jayson Lynch
2021	A	`conf`	The Power of Random Symmetry-Breaking in Nakamoto Consensus. DISC Lili Su, Quanquan C. Liu, Neha Narula
2021	J	`jnl`	The Power of Random Symmetry-Breaking in Nakamoto Consensus. CoRR Lili Su, Quanquan C. Liu, Neha Narula
2020	J	`jnl`	A Lower Bound for Byzantine Agreement and Consensus for Adaptive Adversaries using VDFs. CoRR Thaddeus Dryja, Quanquan C. Liu, Neha Narula
2020	B	`conf`	Closing the Gap Between Cache-oblivious and Cache-adaptive Analysis. SPAA Michael A. Bender, Rezaul Alam Chowdhury, Rathish Das, Rob Johnson, William Kuszmaul, Andrea Lincoln, Quanquan C. Liu, Jayson Lynch, Helen Xu
2020	J	`jnl`	Dynamic Distributed MIS with Improved Bounds. CoRR Shiri Antaki, Quanquan C. Liu, Shay Solomon
2020	J	`jnl`	Parallel Algorithms for Small Subgraph Counting. CoRR Amartya Shankha Biswas, Talya Eden, Quanquan C. Liu, Slobodan Mitrovic, Ronitt Rubinfeld
2020	J	`jnl`	Parallel Batch-Dynamic k-Clique Counting. CoRR Laxman Dhulipala, Quanquan C. Liu, Julian Shun
2020	J	`jnl`	Tatamibari is NP-complete. CoRR Aviv Adler, Jeffrey Bosboom, Erik D. Demaine, Martin L. Demaine, Quanquan C. Liu, Jayson Lynch
2019	J	`jnl`	Fully Dynamic (Δ+1)-Coloring in Constant Update Time. CoRR Sayan Bhattacharya, Fabrizio Grandoni, Janardhan Kulkarni, Quanquan C. Liu, Shay Solomon
2019	A	`conf`	Structural Rounding: Approximation Algorithms for Graphs Near an Algorithmically Tractable Class. ESA Erik D. Demaine, Timothy D. Goodrich, Kyle Kloster, Brian Lavallee, Quanquan C. Liu, Blair D. Sullivan, Ali Vakilian, Andrew van der Poel
2018	B	`conf`	Cache-Adaptive Exploration: Experimental Results and Scan-Hiding for Adaptivity. SPAA Andrea Lincoln, Quanquan C. Liu, Jayson Lynch, Helen Xu
2018	A	`conf`	Fine-grained I/O Complexity via Reductions: New Lower Bounds, Faster Algorithms, and a Time Hierarchy. ITCS Erik D. Demaine, Andrea Lincoln, Quanquan C. Liu, Jayson Lynch, Virginia Vassilevska Williams
2018	B	`conf`	Red-Blue Pebble Game: Complexity of Computing the Trade-Off between Cache Size and Memory Transfers. SPAA Erik D. Demaine, Quanquan C. Liu
2018	J	`jnl`	Static-Memory-Hard Functions and Nonlinear Space-Time Tradeoffs via Pebbling. CoRR Thaddeus Dryja, Quanquan C. Liu, Sunoo Park
2018	J	`jnl`	Static-Memory-Hard Functions and Nonlinear Space-Time Tradeoffs via Pebbling. IACR Cryptol. ePrint Arch. Thaddeus Dryja, Quanquan C. Liu, Sunoo Park
2018	—	`conf`	Static-Memory-Hard Functions, and Modeling the Cost of Space vs. Time. TCC (1) Thaddeus Dryja, Quanquan C. Liu, Sunoo Park
2018	J	`jnl`	Structural Rounding: Approximation Algorithms for Graphs Near an Algorithmically Tractable Class. CoRR Erik D. Demaine, Timothy D. Goodrich, Kyle Kloster, Brian Lavallee, Quanquan C. Liu, Blair D. Sullivan, Ali Vakilian, Andrew van der Poel
2017	J	`jnl`	Arboral satisfaction: Recognition and LP approximation. Inf. Process. Lett. Erik D. Demaine, Varun Ganesan, Vladislav Kontsevoi, Qipeng Liu, Quanquan C. Liu, Fermi Ma, Ofir Nachum, Aaron Sidford, Erik Waingarten, Daniel Ziegler
2017	J	`jnl`	Fine-Grained I/O Complexity via Reductions: New lower bounds, faster algorithms, and a time hierarchy. CoRR Erik D. Demaine, Andrea Lincoln, Quanquan C. Liu, Jayson Lynch, Virginia Vassilevska Williams
2017	B	`conf`	Inapproximability of the Standard Pebble Game and Hard to Pebble Graphs. WADS Erik D. Demaine, Quanquan C. Liu
2017	J	`jnl`	Inapproximability of the Standard Pebble Game and Hard to Pebble Graphs. CoRR Erik D. Demaine, Quanquan C. Liu
2017	A	`conf`	Upward Partitioned Book Embeddings. GD Hugo A. Akitaya, Erik D. Demaine, Adam Hesterberg, Quanquan C. Liu
2017	J	`jnl`	Upward Partitioned Book Embeddings. CoRR Hugo A. Akitaya, Erik D. Demaine, Adam Hesterberg, Quanquan C. Liu
2015	A	`conf`	Kibitz: End-to-End Recommendation System Builder. RecSys Quanquan C. Liu, David R. Karger
2015	B	`conf`	Polylogarithmic Fully Retroactive Priority Queues via Hierarchical Checkpointing. WADS Erik D. Demaine, Tim Kaler, Quanquan C. Liu, Aaron Sidford, Adam Yedidia