Pasin Manurangsi
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
70
Venues
22
Active years
2013–2026
Best venue rank
A*
Where they publish
- A*IJCAI10 papers
- A*AAAI8 papers
- A*COLT8 papers
- A*ICML7 papers
- A*ICALP5 papers
- A*SODA5 papers
- AAISTATS3 papers
- A*ICLR3 papers
- A*STOC3 papers
- AESA3 papers
- BSAGT2 papers
- A*FOCS2 papers
- BWAOA2 papers
- A*WWW1 paper
- A*KDD1 paper
- A*PODS1 paper
- A*CCS1 paper
- A*EMNLP1 paper
- BALT1 paper
- A*CRYPTO1 paper
- A*EuroCrypt1 paper
- BIPCO1 paper
Papers
70 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | Fair Allocation of Indivisible Goods with Variable Groups. | Paul Glz, Ayumi Igarashi, Pasin Manurangsi, Warut Suksompong |
| 2026 | AAAI | Improved Differentially Private Algorithms for Rank Aggregation. | Quentin Hillebrand, Pasin Manurangsi, Vorapong Suppakitpaisarn, Phanu Vajanopath |
| 2026 | COLT | Fixed-Parameter Tractability of Private Synthetic Data Generation. | Badih Ghazi, Cristbal Guzmn, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi |
| 2026 | COLT | Nearly Linear-Time User-Level DP-SCO with Optimal Rates. | Badih Ghazi, Ravi Kumar, Daogao Liu, Pasin Manurangsi |
| 2025 | AISTATS | Balls-and-Bins Sampling for DP-SGD. | Lynn Chua, Badih Ghazi, Charlie Harrison, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang |
| 2025 | COLT | PREM: Privately Answering Statistical Queries with Relative Error. | Badih Ghazi, Cristbal Guzmn, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Sushant Sachdeva |
| 2025 | ICLR | Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy. | Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang |
| 2025 | IJCAI | Dividing Conflicting Items Fairly. | Ayumi Igarashi, Pasin Manurangsi, Hirotaka Yoneda |
| 2025 | IJCAI | Asymptotic Fair Division: Chores Are Easier Than Goods. | Pasin Manurangsi, Warut Suksompong |
| 2025 | IJCAI | Asymptotic Analysis of Weighted Fair Division. | Pasin Manurangsi, Warut Suksompong, Tomohiko Yokoyama |
| 2024 | COLT | On Convex Optimization with Semi-Sensitive Features. | Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang |
| 2024 | ICLR | LabelDP-Pro: Learning with Label Differential Privacy via Projections. | Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang |
| 2024 | ICML | How Private are DP-SGD Implementations? | Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang |
| 2024 | ICML | Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization. | Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon |
| 2024 | IJCAI | Ordinal Maximin Guarantees for Group Fair Division. | Pasin Manurangsi, Warut Suksompong |
| 2024 | WWW | Privacy in Web Advertising: Analytics and Modeling. | Badih Ghazi, Ravi Kumar, Pasin Manurangsi |
| 2024 | SAGT | Complexity of Round-Robin Allocation with Potentially Noisy Queries. | Zihan Li, Pasin Manurangsi, Jonathan Scarlett, Warut Suksompong |
| 2023 | AAAI | Differentially Private Heatmaps. | Badih Ghazi, Junfeng He, Kai Kohlhoff, Ravi Kumar, Pasin Manurangsi, Vidhya Navalpakkam, Nachiappan Valliappan |
| 2023 | AAAI | Differentially Private Fair Division. | Pasin Manurangsi, Warut Suksompong |
| 2023 | COLT | Ticketed Learning-Unlearning Schemes. | Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang |
| 2023 | FOCS | Towards Separating Computational and Statistical Differential Privacy. | Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar, Pasin Manurangsi |
| 2023 | ICALP | On Differentially Private Counting on Trees. | Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Kewen Wu |
| 2023 | ICLR | Regression with Label Differential Privacy. | Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang |
| 2023 | ICML | On User-Level Private Convex Optimization. | Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang |
| 2023 | KDD | Privacy in Advertising: Analytics and Modeling. | Badih Ghazi, Ravi Kumar, Pasin Manurangsi |
| 2023 | PODS | Differentially Private Data Release over Multiple Tables. | Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi |
| 2023 | SODA | Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds. | Justin Y. Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Shyam Narayanan, Jelani Nelson, Yinzhan Xu |
| 2022 | AAAI | Private Rank Aggregation in Central and Local Models. | Daniel Alabi, Badih Ghazi, Ravi Kumar, Pasin Manurangsi |
| 2022 | AAAI | The Price of Justified Representation. | Edith Elkind, Piotr Faliszewski, Ayumi Igarashi, Pasin Manurangsi, Ulrike Schmidt-Kraepelin, Warut Suksompong |
| 2022 | AISTATS | Hardness of Learning a Single Neuron with Adversarial Label Noise. | Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren |
| 2022 | CCS | Distributed, Private, Sparse Histograms in the Two-Server Model. | James Bell, Adri Gascn, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Mariana Raykova, Phillipp Schoppmann |
| 2022 | COLT | Private Robust Estimation by Stabilizing Convex Relaxations. | Pravesh Kothari, Pasin Manurangsi, Ameya Velingker |
| 2022 | EMNLP | Large-Scale Differentially Private BERT. | Rohan Anil, Badih Ghazi, Vineet Gupta, Ravi Kumar, Pasin Manurangsi |
| 2022 | ICALP | Improved Approximation Algorithms and Lower Bounds for Search-Diversification Problems. | Amir Abboud, Vincent Cohen-Addad, Euiwoong Lee, Pasin Manurangsi |
| 2022 | ICML | Faster Privacy Accounting via Evolving Discretization. | Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi |
| 2022 | IJCAI | Fixing Knockout Tournaments With Seeds. | Pasin Manurangsi, Warut Suksompong |
| 2022 | SAGT | Justifying Groups in Multiwinner Approval Voting. | Edith Elkind, Piotr Faliszewski, Ayumi Igarashi, Pasin Manurangsi, Ulrike Schmidt-Kraepelin, Warut Suksompong |
| 2021 | AISTATS | Robust and Private Learning of Halfspaces. | Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen |
| 2021 | ALT | Near-tight closure b ounds for the Littlestone and threshold dimensions. | Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi |
| 2021 | COLT | On Avoiding the Union Bound When Answering Multiple Differentially Private Queries. | Badih Ghazi, Ravi Kumar, Pasin Manurangsi |
| 2021 | ICML | Locally Private k-Means in One Round. | Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi |
| 2021 | ICML | Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message. | Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha |
| 2021 | IJCAI | Generalized Kings and Single-Elimination Winners in Random Tournaments. | Pasin Manurangsi, Warut Suksompong |
| 2021 | IJCAI | Almost Envy-Freeness for Groups: Improved Bounds via Discrepancy Theory. | Pasin Manurangsi, Warut Suksompong |
| 2021 | STOC | Sample-efficient proper PAC learning with approximate differential privacy. | Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi |
| 2021 | WAOA | Tight Inapproximability of Minimum Maximal Matching on Bipartite Graphs and Related Problems. | Szymon Dudycz, Pasin Manurangsi, Jan Marcinkowski |
| 2020 | CRYPTO | Nearly Optimal Robust Secret Sharing Against Rushing Adversaries. | Pasin Manurangsi, Akshayaram Srinivasan, Prashant Nalini Vasudevan |
| 2020 | EuroCrypt | Private Aggregation from Fewer Anonymous Messages. | Badih Ghazi, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker |
| 2020 | ICML | Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead. | Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh |
| 2020 | IJCAI | Tight Approximation for Proportional Approval Voting. | Szymon Dudycz, Pasin Manurangsi, Jan Marcinkowski, Krzysztof Sornat |
| 2020 | SODA | Tight Running Time Lower Bounds for Strong Inapproximability of Maximum | Pasin Manurangsi |
| 2020 | WAOA | To Close Is Easier Than To Open: Dual Parameterization To k-Median. | Jaroslaw Byrka, Szymon Dudycz, Pasin Manurangsi, Jan Marcinkowski, Michal Wlodarczyk |
| 2019 | AAAI | Approximation and Hardness of Shift-Bribery. | Piotr Faliszewski, Pasin Manurangsi, Krzysztof Sornat |
| 2019 | AAAI | When Do Envy-Free Allocations Exist? | Pasin Manurangsi, Warut Suksompong |
| 2019 | IJCAI | The Price of Fairness for Indivisible Goods. | Xiaohui Bei, Xinhang Lu, Pasin Manurangsi, Warut Suksompong |
| 2019 | SODA | Losing Treewidth by Separating Subsets. | Anupam Gupta, Euiwoong Lee, Jason Li, Pasin Manurangsi, Michal Wlodarczyk |
| 2019 | SODA | A Note on Max k-Vertex Cover: Faster FPT-AS, Smaller Approximate Kernel and Improved Approximation. | Pasin Manurangsi |
| 2018 | ESA | Average Whenever You Meet: Opportunistic Protocols for Community Detection. | Luca Becchetti, Andrea Clementi, Pasin Manurangsi, Emanuele Natale, Francesco Pasquale, Prasad Raghavendra, Luca Trevisan |
| 2018 | ESA | Parameterized Approximation Algorithms for Bidirected Steiner Network Problems. | Rajesh Chitnis, Andreas Emil Feldmann, Pasin Manurangsi |
| 2018 | ICALP | Parameterized Intractability of Even Set and Shortest Vector Problem from Gap-ETH. | Arnab Bhattacharyya, Suprovat Ghoshal, Karthik C. S., Pasin Manurangsi |
| 2018 | STOC | On the parameterized complexity of approximating dominating set. | Karthik C. S., Bundit Laekhanukit, Pasin Manurangsi |
| 2017 | COLT | Inapproximability of VC Dimension and Littlestone's Dimension. | Pasin Manurangsi, Aviad Rubinstein |
| 2017 | FOCS | From Gap-ETH to FPT-Inapproximability: Clique, Dominating Set, and More. | Parinya Chalermsook, Marek Cygan, Guy Kortsarz, Bundit Laekhanukit, Pasin Manurangsi, Danupon Nanongkai, Luca Trevisan |
| 2017 | ICALP | Inapproximability of Maximum Edge Biclique, Maximum Balanced Biclique and Minimum k-Cut from the Small Set Expansion Hypothesis. | Pasin Manurangsi |
| 2017 | ICALP | A Birthday Repetition Theorem and Complexity of Approximating Dense CSPs. | Pasin Manurangsi, Prasad Raghavendra |
| 2017 | IJCAI | Computing an Approximately Optimal Agreeable Set of Items. | Pasin Manurangsi, Warut Suksompong |
| 2017 | IPCO | An Improved Integrality Gap for the Călinescu-Karloff-Rabani Relaxation for Multiway Cut. | Haris Angelidakis, Yury Makarychev, Pasin Manurangsi |
| 2017 | SODA | Approximation Algorithms for Label Cover and The Log-Density Threshold. | Eden Chlamtc, Pasin Manurangsi, Dana Moshkovitz, Aravindan Vijayaraghavan |
| 2017 | STOC | Almost-polynomial ratio ETH-hardness of approximating densest k-subgraph. | Pasin Manurangsi |
| 2013 | ESA | Improved Approximation Algorithms for Projection Games - (Extended Abstract). | Pasin Manurangsi, Dana Moshkovitz |