Pasin Manurangsi

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 239

Top Venues

CoRR

NeurIPS

ITCS

Electron. Colloquium Comput. Complex.

Publications

Karthik C. S., Pasin Manurangsi
On Inapproximability of Reconfiguration Problems: PSPACE-Hardness and some Tight NP-Hardness Results. Electron. Colloquium Comput. Complex. (2024)
John Delaney, Badih Ghazi, Charlie Harrison, Christina Ilvento, Ravi Kumar, Pasin Manurangsi, Martin Pál, Karthik Prabhakar, Mariana Raykova
Differentially Private Ad Conversion Measurement. Proc. Priv. Enhancing Technol. 2024 (2) (2024)
Hidayet Aksu, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon, Avinash V. Varadarajan
Summary Reports Optimization in the Privacy Sandbox Attribution Reporting API. Proc. Priv. Enhancing Technol. 2024 (4) (2024)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
On Convex Optimization with Semi-Sensitive Features. COLT (2024)
Euiwoong Lee, Pasin Manurangsi
Hardness of Approximating Bounded-Degree Max 2-CSP and Independent Set on k-Claw-Free Graphs. ITCS (2024)
Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Daogao Liu, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning. CoRR (2024)
Pasin Manurangsi
Improved FPT Approximation Scheme and Approximate Kernel for Biclique-Free Max k-Weight SAT: Greedy Strikes Back. CoRR (2024)
Pasin Manurangsi
Improved Lower Bound for Differentially Private Facility Location. CoRR (2024)
Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
How Private is DP-SGD? CoRR (2024)
Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
LabelDP-Pro: Learning with Label Differential Privacy via Projections. ICLR (2024)
John Delaney, Badih Ghazi, Charlie Harrison, Christina Ilvento, Ravi Kumar, Pasin Manurangsi, Martin Pal, Karthik Prabhakar, Mariana Raykova
Differentially Private Ad Conversion Measurement. CoRR (2024)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi
Privacy in Web Advertising: Analytics and Modeling. WWW (Companion Volume) (2024)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
On Convex Optimization with Semi-Sensitive Features. CoRR (2024)
Karthik C. S., Euiwoong Lee, Pasin Manurangsi
On Equivalence of Parameterized Inapproximability of k-Median, k-Max-Coverage, and 2-CSP. CoRR (2024)
Pasin Manurangsi
A note on hardness of computing recursive teaching dimension. Inf. Process. Lett. 183 (2024)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization. CoRR (2024)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
On Computing Pairwise Statistics with Local Differential Privacy. CoRR (2024)
Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
Training Differentially Private Ad Prediction Models with Semi-Sensitive Features. CoRR (2024)
Ilan Doron-Arad, Ariel Kulik, Pasin Manurangsi
Fine Grained Lower Bounds for Multidimensional Knapsack. CoRR (2024)
Zihan Li, Pasin Manurangsi, Jonathan Scarlett, Warut Suksompong
Complexity of Round-Robin Allocation with Potentially Noisy Queries. CoRR (2024)
Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang
Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models. CoRR (2024)
Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Differentially Private Optimization with Sparse Gradients. CoRR (2024)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi
Pure-DP Aggregation in the Shuffle Model: Error-Optimal and Communication-Efficient. ITC (2024)
Pasin Manurangsi, Warut Suksompong
Ordinal Maximin Guarantees for Group Fair Division. CoRR (2024)
Badih Ghazi, Junfeng He, Kai Kohlhoff, Ravi Kumar, Pasin Manurangsi, Vidhya Navalpakkam, Nachiappan Valliappan
Differentially Private Heatmaps. AAAI (2023)
Pasin Manurangsi, Erel Segal-Halevi, Warut Suksompong
On maximum bipartite matching with separation. Inf. Process. Lett. 182 (2023)
Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Separating Computational and Statistical Differential Privacy (Under Plausible Assumptions). CoRR (2023)
Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi
On Differentially Private Sampling from Gaussian and Product Distributions. CoRR (2023)
Pasin Manurangsi
Improved Inapproximability of VC Dimension and Littlestone's Dimension via (Unbalanced) Biclique. ITCS (2023)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Raghu Meka, Pasin Manurangsi, Chiyuan Zhang
On User-Level Private Convex Optimization. CoRR (2023)
Amir Abboud, Vincent Cohen-Addad, Euiwoong Lee, Pasin Manurangsi
-Center in Sparse Graphs. SOSA (2023)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang
Ticketed Learning-Unlearning Schemes. COLT (2023)
Ashwinkumar Badanidiyuru Varadaraja, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
Optimal Unbiased Randomizers for Regression with Label Differential Privacy. NeurIPS (2023)
Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
Private Ad Modeling with DP-SGD. AdKDD@KDD (2023)
Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi
Differentially Private Data Release over Multiple Tables. PODS (2023)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash Varadarajan, Chiyuan Zhang
Regression with Label Differential Privacy. ICLR (2023)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi
Privacy in Advertising: Analytics and Modeling. KDD (2023)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
On User-Level Private Convex Optimization. ICML (2023)
Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Towards Separating Computational and Statistical Differential Privacy. FOCS (2023)
Matthew Dawson, Badih Ghazi, Pritish Kamath, Kapil Kumar, Ravi Kumar, Bo Luan, Pasin Manurangsi, Nishanth Mundru, Harikesh Nair, Adam Sealfon, Shengyu Zhu
Optimizing Hierarchical Queries for the Attribution Reporting API. CoRR (2023)
Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
Sparsity-Preserving Differentially Private Training of Large Embedding Models. NeurIPS (2023)
Pasin Manurangsi, Warut Suksompong
Fixing knockout tournaments with seeds. Discret. Appl. Math. 339 (2023)
Badih Ghazi, Ravi Kumar, Jelani Nelson, Pasin Manurangsi
Private Counting of Distinct and k-Occurring Items in Time Windows. ITCS (2023)
Matthew Dawson, Badih Ghazi, Pritish Kamath, Kapil Kumar, Ravi Kumar, Bo Luan, Pasin Manurangsi, Nishanth Mundru, Harikesh Nair, Adam Sealfon, Shengyu Zhu
Optimizing Hierarchical Queries for the Attribution Reporting API. AdKDD@KDD (2023)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou
Differentially Private Aggregation via Imperfect Shuffling. CoRR (2023)
Pasin Manurangsi, Erel Segal-Halevi, Warut Suksompong
On Maximum Bipartite Matching with Separation. CoRR (2023)
Euiwoong Lee, Pasin Manurangsi
Hardness of Approximating Bounded-Degree Max 2-CSP and Independent Set on k-Claw-Free Graphs. CoRR (2023)
Hidayet Aksu, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon, Avinash V. Varadarajan
Summary Reports Optimization in the Privacy Sandbox Attribution Reporting API. CoRR (2023)
Pasin Manurangsi, Warut Suksompong
Differentially Private Fair Division. AAAI (2023)
Karthik C. S., Pasin Manurangsi
On Inapproximability of Reconfiguration Problems: PSPACE-Hardness and some Tight NP-Hardness Results. CoRR (2023)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi
Pure-DP Aggregation in the Shuffle Model: Error-Optimal and Communication-Efficient. CoRR (2023)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
User-Level Differential Privacy With Few Examples Per User. CoRR (2023)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Kewen Wu
On Differentially Private Counting on Trees. ICALP (2023)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
On Computing Pairwise Statistics with Local Differential Privacy. NeurIPS (2023)
Pasin Manurangsi
A Note on Hardness of Computing Recursive Teaching Dimension. CoRR (2023)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang
Ticketed Learning-Unlearning Schemes. CoRR (2023)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou
Differentially Private Aggregation via Imperfect Shuffling. ITC (2023)
Justin Y. Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Shyam Narayanan, Jelani Nelson, Yinzhan Xu
Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds. SODA (2023)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
User-Level Differential Privacy With Few Examples Per User. NeurIPS (2023)
Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi
Differentially Private Data Release over Multiple Tables. CoRR (2023)
Edith Elkind, Piotr Faliszewski, Ayumi Igarashi, Pasin Manurangsi, Ulrike Schmidt-Kraepelin, Warut Suksompong
Justifying groups in multiwinner approval voting. Theor. Comput. Sci. 969 (2023)
Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
Sparsity-Preserving Differentially Private Training of Large Embedding Models. CoRR (2023)
Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi
On Differentially Private Sampling from Gaussian and Product Distributions. NeurIPS (2023)
Ashwinkumar Badanidiyuru, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
Optimal Unbiased Randomizers for Regression with Label Differential Privacy. CoRR (2023)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thomas Steinke
Algorithms with More Granular Differential Privacy Guarantees. ITCS (2023)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Faster Privacy Accounting via Evolving Discretization. ICML (2022)
Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi, Lisheng Ren
Cryptographic Hardness of Learning Halfspaces with Massart Noise. CoRR (2022)
Amir Abboud, Vincent Cohen-Addad, Euiwoong Lee, Pasin Manurangsi
Improved Approximation Algorithms and Lower Bounds for Search-Diversification Problems. ICALP (2022)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson
Private Counting of Distinct and k-Occurring Items in Time Windows. CoRR (2022)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thomas Steinke
Algorithms with More Granular Differential Privacy Guarantees. CoRR (2022)
Vadym Doroshenko, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions. CoRR (2022)
Pasin Manurangsi
Tight Bounds for Differentially Private Anonymized Histograms. SOSA (2022)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Anonymized Histograms in Intermediate Privacy Models. CoRR (2022)
Pravesh Kothari, Pasin Manurangsi, Ameya Velingker
Private Robust Estimation by Stabilizing Convex Relaxations. COLT (2022)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Faster Privacy Accounting via Evolving Discretization. CoRR (2022)
Daniel Alabi, Badih Ghazi, Ravi Kumar, Pasin Manurangsi
Private Rank Aggregation in Central and Local Models. AAAI (2022)
Pasin Manurangsi, Warut Suksompong
Fixing Knockout Tournaments With Seeds. IJCAI (2022)
Pasin Manurangsi
Improved Inapproximability of VC Dimension and Littlestone's Dimension via (Unbalanced) Biclique. CoRR (2022)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Kewen Wu
On Differentially Private Counting on Trees. CoRR (2022)
Badih Ghazi, Neel Kamal, Ravi Kumar, Pasin Manurangsi, Annika Zhang
Private Aggregation of Trajectories. Proc. Priv. Enhancing Technol. 2022 (4) (2022)
Pasin Manurangsi, Preetum Nakkiran, Luca Trevisan
. Theory Comput. 18 (2022)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson
Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds. CoRR (2022)
Badih Ghazi, Ben Kreuter, Ravi Kumar, Pasin Manurangsi, Jiayu Peng, Evgeny Skvortsov, Yao Wang, Craig Wright
Multiparty Reach and Frequency Histogram: Private, Secure, and Practical. Proc. Priv. Enhancing Technol. 2022 (1) (2022)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash Varadarajan, Chiyuan Zhang
Regression with Label Differential Privacy. CoRR (2022)
James Bell, Adrià Gascón, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Mariana Raykova, Phillipp Schoppmann
Distributed, Private, Sparse Histograms in the Two-Server Model. IACR Cryptol. ePrint Arch. 2022 (2022)
Rohan Anil, Badih Ghazi, Vineet Gupta, Ravi Kumar, Pasin Manurangsi
Large-Scale Differentially Private BERT. EMNLP (Findings) (2022)
Edith Elkind, Piotr Faliszewski, Ayumi Igarashi, Pasin Manurangsi, Ulrike Schmidt-Kraepelin, Warut Suksompong
Justifying Groups in Multiwinner Approval Voting. SAGT (2022)
Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren
Hardness of Learning a Single Neuron with Adversarial Label Noise. AISTATS (2022)
Badih Ghazi, Junfeng He, Kai Kohlhoff, Ravi Kumar, Pasin Manurangsi, Vidhya Navalpakkam, Nachiappan Valliappan
Differentially Private Heatmaps. CoRR (2022)
James Bell, Adrià Gascón, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Mariana Raykova, Phillipp Schoppmann
Distributed, Private, Sparse Histograms in the Two-Server Model. CCS (2022)
Edith Elkind, Piotr Faliszewski, Ayumi Igarashi, Pasin Manurangsi, Ulrike Schmidt-Kraepelin, Warut Suksompong
The Price of Justified Representation. AAAI (2022)
Vadym Doroshenko, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions. Proc. Priv. Enhancing Technol. 2022 (4) (2022)
Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren
Cryptographic Hardness of Learning Halfspaces with Massart Noise. NeurIPS (2022)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Private Isotonic Regression. NeurIPS (2022)
Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash Varadarajan, Chiyuan Zhang
Private Ad Modeling with DP-SGD. CoRR (2022)
Pasin Manurangsi, Warut Suksompong
Almost envy-freeness for groups: Improved bounds via discrepancy theory. Theor. Comput. Sci. 930 (2022)
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Anonymized Histograms in Intermediate Privacy Models. NeurIPS (2022)
Pasin Manurangsi, Warut Suksompong
Fixing Knockout Tournaments With Seeds. CoRR (2022)
Amir Abboud, Vincent Cohen-Addad, Euiwoong Lee, Pasin Manurangsi
Improved Approximation Algorithms and Lower Bounds for Search-Diversification Problems. CoRR (2022)
Pasin Manurangsi, Warut Suksompong
Generalized kings and single-elimination winners in random tournaments. Auton. Agents Multi Agent Syst. 36 (1) (2022)

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Publication Activity (10 Years)

Top Topics

Top Venues

Pasin Manurangsi