Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDPasin Manurangsi
พศิน มนูรังษี
Person information
- affiliation: Google, Mountain View, CA, USA
- affiliation: University of California, Berkeley, USA
- unicode name: พศิน มนูรังษี
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
Books and Theses
- 2019
[b1]Pasin Manurangsi:
Approximation and Hardness: Beyond P and NP. University of California, Berkeley, USA, 2019
Journal Articles
- 2024
- [j30]Pasin Manurangsi:
A note on hardness of computing recursive teaching dimension. Inf. Process. Lett. 183: 106429 (2024) - 2023
- [j29]Pasin Manurangsi, Warut Suksompong:
Fixing knockout tournaments with seeds. Discret. Appl. Math. 339: 21-35 (2023) - [j28]Pasin Manurangsi, Erel Segal-Halevi, Warut Suksompong:
On maximum bipartite matching with separation. Inf. Process. Lett. 182: 106388 (2023) - [j27]Edith Elkind, Piotr Faliszewski
, Ayumi Igarashi, Pasin Manurangsi, Ulrike Schmidt-Kraepelin, Warut Suksompong:
Justifying groups in multiwinner approval voting. Theor. Comput. Sci. 969: 114039 (2023) - 2022
- [j26]Pasin Manurangsi, Warut Suksompong:
Generalized kings and single-elimination winners in random tournaments. Auton. Agents Multi Agent Syst. 36(1): 28 (2022) - [j25]Paul W. Goldberg, Alexandros Hollender, Ayumi Igarashi, Pasin Manurangsi, Warut Suksompong:
Consensus Halving for Sets of Items. Math. Oper. Res. 47(4): 3357-3379 (2022) - [j24]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): 373-395 (2022) - [j23]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): 552-570 (2022) - [j22]Badih Ghazi, Neel Kamal, Ravi Kumar, Pasin Manurangsi, Annika Zhang:
Private Aggregation of Trajectories. Proc. Priv. Enhancing Technol. 2022(4): 626-644 (2022) - [j21]Pasin Manurangsi, Warut Suksompong:
Almost envy-freeness for groups: Improved bounds via discrepancy theory. Theor. Comput. Sci. 930: 179-195 (2022) - [j20]Pasin Manurangsi, Preetum Nakkiran, Luca Trevisan:
Near-Optimal NP-Hardness of Approximating Max k-CSPR. Theory Comput. 18: 1-29 (2022) - 2021
- [j19]Piotr Faliszewski, Pasin Manurangsi, Krzysztof Sornat:
Approximation and hardness of Shift-Bribery. Artif. Intell. 298: 103520 (2021) - [j18]Pasin Manurangsi:
Linear discrepancy is Π2-hard to approximate. Inf. Process. Lett. 172: 106164 (2021) - [j17]Arnab Bhattacharyya, Édouard Bonnet, László Egri, Suprovat Ghoshal, Karthik C. S., Bingkai Lin, Pasin Manurangsi, Dániel Marx:
Parameterized Intractability of Even Set and Shortest Vector Problem. J. ACM 68(3): 16:1-16:40 (2021) - [j16]Xiaohui Bei, Xinhang Lu, Pasin Manurangsi, Warut Suksompong:
The Price of Fairness for Indivisible Goods. Theory Comput. Syst. 65(7): 1069-1093 (2021) - [j15]Naoyuki Kamiyama, Pasin Manurangsi, Warut Suksompong:
On the complexity of fair house allocation. Oper. Res. Lett. 49(4): 572-577 (2021) - [j14]Pasin Manurangsi, Warut Suksompong:
Closing Gaps in Asymptotic Fair Division. SIAM J. Discret. Math. 35(2): 668-706 (2021) - [j13]Rajesh Chitnis, Andreas Emil Feldmann, Pasin Manurangsi:
Parameterized Approximation Algorithms for Bidirected Steiner Network Problems. ACM Trans. Algorithms 17(2): 12:1-12:68 (2021) - 2020
- [j12]Andreas Emil Feldmann, Karthik C. S., Euiwoong Lee, Pasin Manurangsi:
A Survey on Approximation in Parameterized Complexity: Hardness and Algorithms. Algorithms 13(6): 146 (2020) - [j11]Karthik C. S., Pasin Manurangsi:
On Closest Pair in Euclidean Metric: Monochromatic is as Hard as Bichromatic. Comb. 40(4): 539-573 (2020) - [j10]Parinya Chalermsook, Marek Cygan, Guy Kortsarz, Bundit Laekhanukit, Pasin Manurangsi, Danupon Nanongkai, Luca Trevisan:
From Gap-Exponential Time Hypothesis to Fixed Parameter Tractable Inapproximability: Clique, Dominating Set, and More. SIAM J. Comput. 49(4): 772-810 (2020) - [j9]Noga Alon, Jonathan D. Cohen, Thomas L. Griffiths, Pasin Manurangsi, Daniel Reichman, Igor Shinkar, Tal Wagner, Alexander Y. Ku:
Multitasking Capacity: Hardness Results and Improved Constructions. SIAM J. Discret. Math. 34(1): 885-903 (2020) - [j8]Pasin Manurangsi, Warut Suksompong:
When Do Envy-Free Allocations Exist? SIAM J. Discret. Math. 34(3): 1505-1521 (2020) - 2019
- [j7]Pasin Manurangsi, Warut Suksompong:
Computing a small agreeable set of indivisible items. Artif. Intell. 268: 96-114 (2019) - [j6]Pasin Manurangsi:
A note on degree vs gap of Min-Rep Label Cover and improved inapproximability for connectivity problems. Inf. Process. Lett. 145: 24-29 (2019) - [j5]Karthik C. S., Bundit Laekhanukit, Pasin Manurangsi:
On the Parameterized Complexity of Approximating Dominating Set. J. ACM 66(5): 33:1-33:38 (2019) - 2018
- [j4]Pasin Manurangsi:
Inapproximability of Maximum Biclique Problems, Minimum k-Cut and Densest At-Least-k-Subgraph from the Small Set Expansion Hypothesis. Algorithms 11(1): 10 (2018) - 2017
- [j3]Pasin Manurangsi, Dana Moshkovitz:
Improved Approximation Algorithms for Projection Games. Algorithmica 77(2): 555-594 (2017) - [j2]Jeffrey Bosboom, Erik D. Demaine, Martin L. Demaine, Adam Hesterberg, Pasin Manurangsi, Anak Yodpinyanee:
Even 1 × n Edge-Matching and Jigsaw Puzzles are Really Hard. J. Inf. Process. 25: 682-694 (2017) - [j1]Pasin Manurangsi, Warut Suksompong:
Asymptotic existence of fair divisions for groups. Math. Soc. Sci. 89: 100-108 (2017)
Conference and Workshop Papers
- 2024
- [c89]Euiwoong Lee, Pasin Manurangsi:
Hardness of Approximating Bounded-Degree Max 2-CSP and Independent Set on k-Claw-Free Graphs. ITCS 2024: 71:1-71:17 - 2023
- [c88]Pasin Manurangsi, Warut Suksompong:
Differentially Private Fair Division. AAAI 2023: 5814-5822 - [c87]Badih Ghazi, Junfeng He, Kai Kohlhoff, Ravi Kumar, Pasin Manurangsi, Vidhya Navalpakkam, Nachiappan Valliappan:
Differentially Private Heatmaps. AAAI 2023: 7696-7704 - [c86]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 - [c85]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 - [c84]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou:
Differentially Private Aggregation via Imperfect Shuffling. ITC 2023: 17:1-17:22 - [c83]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang:
Ticketed Learning-Unlearning Schemes. COLT 2023: 5110-5139 - [c82]Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Towards Separating Computational and Statistical Differential Privacy. FOCS 2023: 580-599 - [c81]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Kewen Wu:
On Differentially Private Counting on Trees. ICALP 2023: 66:1-66:18 - [c80]Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang:
Regression with Label Differential Privacy. ICLR 2023 - [c79]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
On User-Level Private Convex Optimization. ICML 2023: 11283-11299 - [c78]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thomas Steinke:
Algorithms with More Granular Differential Privacy Guarantees. ITCS 2023: 54:1-54:24 - [c77]Badih Ghazi, Ravi Kumar, Jelani Nelson, Pasin Manurangsi:
Private Counting of Distinct and k-Occurring Items in Time Windows. ITCS 2023: 55:1-55:24 - [c76]Pasin Manurangsi:
Improved Inapproximability of VC Dimension and Littlestone's Dimension via (Unbalanced) Biclique. ITCS 2023: 85:1-85:18 - [c75]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Privacy in Advertising: Analytics and Modeling. KDD 2023: 5802 - [c74]Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi:
On Differentially Private Sampling from Gaussian and Product Distributions. NeurIPS 2023 - [c73]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 - [c72]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
User-Level Differential Privacy With Few Examples Per User. NeurIPS 2023 - [c71]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon:
On Computing Pairwise Statistics with Local Differential Privacy. NeurIPS 2023 - [c70]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 - [c69]Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi:
Differentially Private Data Release over Multiple Tables. PODS 2023: 207-219 - [c68]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: 5040-5067 - [c67]Amir Abboud, Vincent Cohen-Addad, Euiwoong Lee, Pasin Manurangsi:
On the Fine-Grained Complexity of Approximating k-Center in Sparse Graphs. SOSA 2023: 145-155 - 2022
- [c66]Edith Elkind, Piotr Faliszewski, Ayumi Igarashi, Pasin Manurangsi, Ulrike Schmidt-Kraepelin, Warut Suksompong:
The Price of Justified Representation. AAAI 2022: 4983-4990 - [c65]Daniel Alabi, Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Private Rank Aggregation in Central and Local Models. AAAI 2022: 5984-5991 - [c64]Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren:
Hardness of Learning a Single Neuron with Adversarial Label Noise. AISTATS 2022: 8199-8213 - [c63]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: 307-321 - [c62]Pravesh Kothari, Pasin Manurangsi, Ameya Velingker:
Private Robust Estimation by Stabilizing Convex Relaxations. COLT 2022: 723-777 - [c61]Rohan Anil, Badih Ghazi, Vineet Gupta, Ravi Kumar, Pasin Manurangsi:
Large-Scale Differentially Private BERT. EMNLP (Findings) 2022: 6481-6491 - [c60]Amir Abboud, Vincent Cohen-Addad, Euiwoong Lee, Pasin Manurangsi:
Improved Approximation Algorithms and Lower Bounds for Search-Diversification Problems. ICALP 2022: 7:1-7:18 - [c59]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Faster Privacy Accounting via Evolving Discretization. ICML 2022: 7470-7483 - [c58]Pasin Manurangsi, Warut Suksompong:
Fixing Knockout Tournaments With Seeds. IJCAI 2022: 412-418 - [c57]Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren:
Cryptographic Hardness of Learning Halfspaces with Massart Noise. NeurIPS 2022 - [c56]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Anonymized Histograms in Intermediate Privacy Models. NeurIPS 2022 - [c55]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Private Isotonic Regression. NeurIPS 2022 - [c54]Edith Elkind, Piotr Faliszewski, Ayumi Igarashi, Pasin Manurangsi, Ulrike Schmidt-Kraepelin, Warut Suksompong:
Justifying Groups in Multiwinner Approval Voting. SAGT 2022: 472-489 - [c53]Pasin Manurangsi:
Tight Bounds for Differentially Private Anonymized Histograms. SOSA 2022: 203-213 - 2021
- [c52]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen:
Robust and Private Learning of Halfspaces. AISTATS 2021: 1603-1611 - [c51]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi:
Near-tight closure b ounds for the Littlestone and threshold dimensions. ALT 2021: 686-696 - [c50]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
On Avoiding the Union Bound When Answering Multiple Differentially Private Queries. COLT 2021: 2133-2146 - [c49]Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Locally Private k-Means in One Round. ICML 2021: 1441-1451 - [c48]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha:
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message. ICML 2021: 3692-3701 - [c47]Pasin Manurangsi, Warut Suksompong:
Generalized Kings and Single-Elimination Winners in Random Tournaments. IJCAI 2021: 328-334 - [c46]Pasin Manurangsi, Warut Suksompong:
Almost Envy-Freeness for Groups: Improved Bounds via Discrepancy Theory. IJCAI 2021: 335-341 - [c45]Martin Hoefer, Pasin Manurangsi, Alexandros Psomas:
Algorithmic Persuasion with Evidence. ITCS 2021: 3:1-3:20 - [c44]Pasin Manurangsi, Aviad Rubinstein, Tselil Schramm:
The Strongish Planted Clique Hypothesis and Its Consequences. ITCS 2021: 10:1-10:21 - [c43]Surbhi Goel, Adam R. Klivans, Pasin Manurangsi, Daniel Reichman:
Tight Hardness Results for Training Depth-2 ReLU Networks. ITCS 2021: 22:1-22:14 - [c42]Lijie Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
On Distributed Differential Privacy and Counting Distinct Elements. ITCS 2021: 56:1-56:18 - [c41]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
User-Level Differentially Private Learning via Correlated Sampling. NeurIPS 2021: 20172-20184 - [c40]Sreenivas Gollapudi, Guru Guruganesh, Kostas Kollias, Pasin Manurangsi, Renato Paes Leme, Jon Schneider:
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms. NeurIPS 2021: 22498-22508 - [c39]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang:
Deep Learning with Label Differential Privacy. NeurIPS 2021: 27131-27145 - [c38]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi:
Sample-efficient proper PAC learning with approximate differential privacy. STOC 2021: 183-196 - [c37]Szymon Dudycz, Pasin Manurangsi, Jan Marcinkowski:
Tight Inapproximability of Minimum Maximal Matching on Bipartite Graphs and Related Problems. WAOA 2021: 48-64 - 2020
- [c36]Pasin Manurangsi, Akshayaram Srinivasan, Prashant Nalini Vasudevan:
Nearly Optimal Robust Secret Sharing Against Rushing Adversaries. CRYPTO (3) 2020: 156-185 - [c35]Badih Ghazi, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker:
Private Aggregation from Fewer Anonymous Messages. EUROCRYPT (2) 2020: 798-827 - [c34]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker:
Pure Differentially Private Summation from Anonymous Messages. ITC 2020: 15:1-15:23 - [c33]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh:
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead. ICML 2020: 3505-3514 - [c32]Szymon Dudycz, Pasin Manurangsi, Jan Marcinkowski, Krzysztof Sornat:
Tight Approximation for Proportional Approval Voting. IJCAI 2020: 276-282 - [c31]Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi:
The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise. NeurIPS 2020 - [c30]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Differentially Private Clustering: Tight Approximation Ratios. NeurIPS 2020 - [c29]Pasin Manurangsi:
Tight Running Time Lower Bounds for Strong Inapproximability of Maximum k-Coverage, Unique Set Cover and Related Problems (via t-Wise Agreement Testing Theorem). SODA 2020: 62-81 - [c28]Jaroslaw Byrka, Szymon Dudycz, Pasin Manurangsi, Jan Marcinkowski, Michal Wlodarczyk:
To Close Is Easier Than To Open: Dual Parameterization To k-Median. WAOA 2020: 113-126 - [c27]Paul W. Goldberg, Alexandros Hollender, Ayumi Igarashi, Pasin Manurangsi, Warut Suksompong:
Consensus Halving for Sets of Items. WINE 2020: 384-397 - 2019
- [c26]Piotr Faliszewski, Pasin Manurangsi, Krzysztof Sornat:
Approximation and Hardness of Shift-Bribery. AAAI 2019: 1901-1908 - [c25]Pasin Manurangsi, Warut Suksompong:
When Do Envy-Free Allocations Exist? AAAI 2019: 2109-2116 - [c24]Xiaohui Bei, Xinhang Lu, Pasin Manurangsi, Warut Suksompong:
The Price of Fairness for Indivisible Goods. IJCAI 2019: 81-87 - [c23]Karthik C. S., Pasin Manurangsi:
On Closest Pair in Euclidean Metric: Monochromatic is as Hard as Bichromatic. ITCS 2019: 17:1-17:16 - [c22]Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi:
Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin. NeurIPS 2019: 10473-10484 - [c21]Pasin Manurangsi:
A Note on Max k-Vertex Cover: Faster FPT-AS, Smaller Approximate Kernel and Improved Approximation. SOSA 2019: 15:1-15:21 - [c20]Anupam Gupta, Euiwoong Lee, Jason Li, Pasin Manurangsi, Michal Wlodarczyk:
Losing Treewidth by Separating Subsets. SODA 2019: 1731-1749 - 2018
- [c19]Eden Chlamtác, Pasin Manurangsi:
Sherali-Adams Integrality Gaps Matching the Log-Density Threshold. APPROX-RANDOM 2018: 10:1-10:19 - [c18]Pasin Manurangsi, Luca Trevisan:
Mildly Exponential Time Approximation Algorithms for Vertex Cover, Balanced Separator and Uniform Sparsest Cut. APPROX-RANDOM 2018: 20:1-20:17 - [c17]Luca Becchetti, Andrea Clementi, Pasin Manurangsi, Emanuele Natale, Francesco Pasquale, Prasad Raghavendra, Luca Trevisan:
Average Whenever You Meet: Opportunistic Protocols for Community Detection. ESA 2018: 7:1-7:13 - [c16]Rajesh Chitnis, Andreas Emil Feldmann, Pasin Manurangsi:
Parameterized Approximation Algorithms for Bidirected Steiner Network Problems. ESA 2018: 20:1-20:16 - [c15]Arnab Bhattacharyya, Suprovat Ghoshal, Karthik C. S., Pasin Manurangsi:
Parameterized Intractability of Even Set and Shortest Vector Problem from Gap-ETH. ICALP 2018: 17:1-17:15 - [c14]Irit Dinur, Pasin Manurangsi:
ETH-Hardness of Approximating 2-CSPs and Directed Steiner Network. ITCS 2018: 36:1-36:20 - [c13]Karthik C. S., Bundit Laekhanukit, Pasin Manurangsi:
On the parameterized complexity of approximating dominating set. STOC 2018: 1283-1296 - 2017
- [c12]Pasin Manurangsi, Aviad Rubinstein:
Inapproximability of VC Dimension and Littlestone's Dimension. COLT 2017: 1432-1460 - [c11]Parinya Chalermsook, Marek Cygan, Guy Kortsarz, Bundit Laekhanukit, Pasin Manurangsi, Danupon Nanongkai, Luca Trevisan:
From Gap-ETH to FPT-Inapproximability: Clique, Dominating Set, and More. FOCS 2017: 743-754 - [c10]Pasin Manurangsi, Prasad Raghavendra:
A Birthday Repetition Theorem and Complexity of Approximating Dense CSPs. ICALP 2017: 78:1-78:15 - [c9]Pasin Manurangsi:
Inapproximability of Maximum Edge Biclique, Maximum Balanced Biclique and Minimum k-Cut from the Small Set Expansion Hypothesis. ICALP 2017: 79:1-79:14 - [c8]Pasin Manurangsi, Warut Suksompong:
Computing an Approximately Optimal Agreeable Set of Items. IJCAI 2017: 338-344 - [c7]Haris Angelidakis, Yury Makarychev, Pasin Manurangsi:
An Improved Integrality Gap for the Călinescu-Karloff-Rabani Relaxation for Multiway Cut. IPCO 2017: 39-50 - [c6]Eden Chlamtác, Pasin Manurangsi, Dana Moshkovitz, Aravindan Vijayaraghavan:
Approximation Algorithms for Label Cover and The Log-Density Threshold. SODA 2017: 900-919 - [c5]Pasin Manurangsi:
Almost-polynomial ratio ETH-hardness of approximating densest k-subgraph. STOC 2017: 954-961 - 2016
- [c4]Pasin Manurangsi, Preetum Nakkiran, Luca Trevisan:
Near-Optimal UGC-hardness of Approximating Max k-CSP_R. APPROX-RANDOM 2016: 15:1-15:28 - 2015
- [c3]Pasin Manurangsi, Dana Moshkovitz:
Approximating Dense Max 2-CSPs. APPROX-RANDOM 2015: 396-415 - [c2]Jeffrey Bosboom, Erik D. Demaine, Martin L. Demaine, Jayson Lynch, Pasin Manurangsi, Mikhail Rudoy, Anak Yodpinyanee:
Dissection with the Fewest Pieces is Hard, Even to Approximate. JCDCGG 2015: 37-48 - 2013
- [c1]Pasin Manurangsi, Dana Moshkovitz:
Improved Approximation Algorithms for Projection Games - (Extended Abstract). ESA 2013: 683-694
Informal and Other Publications
- 2024
- [i111]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 abs/2401.15246 (2024) - [i110]Pasin Manurangsi:
Improved Lower Bound for Differentially Private Facility Location. CoRR abs/2403.04874 (2024) - [i109]Pasin Manurangsi:
Improved FPT Approximation Scheme and Approximate Kernel for Biclique-Free Max k-Weight SAT: Greedy Strikes Back. CoRR abs/2403.06335 (2024) - [i108]John Delaney, Badih Ghazi, Charlie Harrison, Christina Ilvento, Ravi Kumar, Pasin Manurangsi, Martin Pal, Karthik Prabhakar, Mariana Raykova:
Differentially Private Ad Conversion Measurement. CoRR abs/2403.15224 (2024) - [i107]Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
How Private is DP-SGD? CoRR abs/2403.17673 (2024) - [i106]Karthik C. S., Pasin Manurangsi:
On Inapproximability of Reconfiguration Problems: PSPACE-Hardness and some Tight NP-Hardness Results. Electron. Colloquium Comput. Complex. TR24: TR24-007 (2024) - 2023
- [i105]Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Separating Computational and Statistical Differential Privacy (Under Plausible Assumptions). CoRR abs/2301.00104 (2023) - [i104]Pasin Manurangsi, Erel Segal-Halevi, Warut Suksompong:
On Maximum Bipartite Matching with Separation. CoRR abs/2303.02283 (2023) - [i103]Badih Ghazi, Pritish Kamath, Ravi Kumar, Raghu Meka, Pasin Manurangsi, Chiyuan Zhang:
On User-Level Private Convex Optimization. CoRR abs/2305.04912 (2023) - [i102]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Pure-DP Aggregation in the Shuffle Model: Error-Optimal and Communication-Efficient. CoRR abs/2305.17634 (2023) - [i101]Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi:
On Differentially Private Sampling from Gaussian and Product Distributions. CoRR abs/2306.12549 (2023) - [i100]Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi:
Differentially Private Data Release over Multiple Tables. CoRR abs/2306.15201 (2023) - [i99]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang:
Ticketed Learning-Unlearning Schemes. CoRR abs/2306.15744 (2023) - [i98]Pasin Manurangsi:
A Note on Hardness of Computing Recursive Teaching Dimension. CoRR abs/2307.09792 (2023) - [i97]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 abs/2308.13510 (2023) - [i96]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou:
Differentially Private Aggregation via Imperfect Shuffling. CoRR abs/2308.14733 (2023) - [i95]Euiwoong Lee, Pasin Manurangsi:
Hardness of Approximating Bounded-Degree Max 2-CSP and Independent Set on k-Claw-Free Graphs. CoRR abs/2309.04099 (2023) - [i94]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
User-Level Differential Privacy With Few Examples Per User. CoRR abs/2309.12500 (2023) - [i93]Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
Sparsity-Preserving Differentially Private Training of Large Embedding Models. CoRR abs/2311.08357 (2023) - [i92]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 abs/2311.13586 (2023) - [i91]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 abs/2312.05659 (2023) - [i90]Karthik C. S., Pasin Manurangsi:
On Inapproximability of Reconfiguration Problems: PSPACE-Hardness and some Tight NP-Hardness Results. CoRR abs/2312.17140 (2023) - 2022
- [i89]Amir Abboud, Vincent Cohen-Addad, Euiwoong Lee, Pasin Manurangsi:
Improved Approximation Algorithms and Lower Bounds for Search-Diversification Problems. CoRR abs/2203.01857 (2022) - [i88]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson:
Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds. CoRR abs/2203.16476 (2022) - [i87]Pasin Manurangsi, Warut Suksompong:
Fixing Knockout Tournaments With Seeds. CoRR abs/2204.11171 (2022) - [i86]Vadym Doroshenko, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions. CoRR abs/2207.04380 (2022) - [i85]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Faster Privacy Accounting via Evolving Discretization. CoRR abs/2207.04381 (2022) - [i84]Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi, Lisheng Ren:
Cryptographic Hardness of Learning Halfspaces with Massart Noise. CoRR abs/2207.14266 (2022) - [i83]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thomas Steinke:
Algorithms with More Granular Differential Privacy Guarantees. CoRR abs/2209.04053 (2022) - [i82]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Private Isotonic Regression. CoRR abs/2210.15175 (2022) - [i81]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Anonymized Histograms in Intermediate Privacy Models. CoRR abs/2210.15178 (2022) - [i80]Pasin Manurangsi:
Improved Inapproximability of VC Dimension and Littlestone's Dimension via (Unbalanced) Biclique. CoRR abs/2211.01443 (2022) - [i79]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson:
Private Counting of Distinct and k-Occurring Items in Time Windows. CoRR abs/2211.11718 (2022) - [i78]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. CoRR abs/2211.11896 (2022) - [i77]Pasin Manurangsi, Warut Suksompong:
Differentially Private Fair Division. CoRR abs/2211.12738 (2022) - [i76]Badih Ghazi, Junfeng He, Kai Kohlhoff, Ravi Kumar, Pasin Manurangsi, Vidhya Navalpakkam, Nachiappan Valliappan:
Differentially Private Heatmaps. CoRR abs/2211.13454 (2022) - [i75]Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang:
Regression with Label Differential Privacy. CoRR abs/2212.06074 (2022) - [i74]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Kewen Wu:
On Differentially Private Counting on Trees. CoRR abs/2212.11967 (2022) - [i73]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: 920 (2022) - 2021
- [i72]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang:
On Deep Learning with Label Differential Privacy. CoRR abs/2102.06062 (2021) - [i71]Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Locally Private k-Means in One Round. CoRR abs/2104.09734 (2021) - [i70]Pasin Manurangsi, Warut Suksompong:
Generalized Kings and Single-Elimination Winners in Random Tournaments. CoRR abs/2105.00193 (2021) - [i69]Pasin Manurangsi, Warut Suksompong:
Almost Envy-Freeness for Groups: Improved Bounds via Discrepancy Theory. CoRR abs/2105.01609 (2021) - [i68]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh:
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead. CoRR abs/2106.04247 (2021) - [i67]Sreenivas Gollapudi, Guru Guruganesh, Kostas Kollias, Pasin Manurangsi, Renato Paes Leme, Jon Schneider:
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms. CoRR abs/2106.04819 (2021) - [i66]Naoyuki Kamiyama, Pasin Manurangsi, Warut Suksompong:
On the Complexity of Fair House Allocation. CoRR abs/2106.06925 (2021) - [i65]Shailesh Bavadekar, Adam Boulanger, John Davis, Damien Desfontaines, Evgeniy Gabrilovich, Krishna Gadepalli, Badih Ghazi, Tague Griffith, Jai Prakash Gupta, Chaitanya Kamath, Dennis Kraft, Ravi Kumar, Akim Kumok, Yael Mayer, Pasin Manurangsi, Arti Patankar, Irippuge Milinda Perera, Chris Scott, Tomer Shekel, Benjamin Miller, Karen Smith, Charlotte Stanton, Mimi Sun, Mark Young, Gregory Wellenius:
Google COVID-19 Vaccination Search Insights: Anonymization Process Description. CoRR abs/2107.01179 (2021) - [i64]Pasin Manurangsi:
Linear Discrepancy is Π2-Hard to Approximate. CoRR abs/2107.01235 (2021) - [i63]Rohan Anil, Badih Ghazi, Vineet Gupta, Ravi Kumar, Pasin Manurangsi:
Large-Scale Differentially Private BERT. CoRR abs/2108.01624 (2021) - [i62]Edith Elkind, Piotr Faliszewski, Ayumi Igarashi, Pasin Manurangsi, Ulrike Schmidt-Kraepelin, Warut Suksompong:
Justifying Groups in Multiwinner Approval Voting. CoRR abs/2108.12949 (2021) - [i61]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha:
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message. CoRR abs/2109.13158 (2021) - [i60]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
User-Level Private Learning via Correlated Sampling. CoRR abs/2110.11208 (2021) - [i59]Pasin Manurangsi:
Tight Bounds for Differentially Private Anonymized Histograms. CoRR abs/2111.03257 (2021) - [i58]Pravesh K. Kothari, Pasin Manurangsi, Ameya Velingker:
Private Robust Estimation by Stabilizing Convex Relaxations. CoRR abs/2112.03548 (2021) - [i57]Edith Elkind, Piotr Faliszewski, Ayumi Igarashi, Pasin Manurangsi, Ulrike Schmidt-Kraepelin, Warut Suksompong:
The Price of Justified Representation. CoRR abs/2112.05994 (2021) - [i56]Daniel Alabi, Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Private Rank Aggregation in Central and Local Models. CoRR abs/2112.14652 (2021) - 2020
- [i55]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker:
Pure Differentially Private Summation from Anonymous Messages. CoRR abs/2002.01919 (2020) - [i54]Pasin Manurangsi, Warut Suksompong:
Closing Gaps in Asymptotic Fair Division. CoRR abs/2004.05563 (2020) - [i53]Andreas Emil Feldmann, Karthik C. S., Euiwoong Lee, Pasin Manurangsi:
A Survey on Approximation in Parameterized Complexity: Hardness and Algorithms. CoRR abs/2006.04411 (2020) - [i52]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi:
Near-tight closure bounds for Littlestone and threshold dimensions. CoRR abs/2007.03668 (2020) - [i51]Paul W. Goldberg, Alexandros Hollender, Ayumi Igarashi, Pasin Manurangsi, Warut Suksompong:
Consensus Halving for Sets of Items. CoRR abs/2007.06754 (2020) - [i50]Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi:
The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise. CoRR abs/2007.15220 (2020) - [i49]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Differentially Private Clustering: Tight Approximation Ratios. CoRR abs/2008.08007 (2020) - [i48]Martin Hoefer, Pasin Manurangsi, Alexandros Psomas:
Algorithmic Persuasion with Evidence. CoRR abs/2008.12626 (2020) - [i47]Lijie Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
On Distributed Differential Privacy and Counting Distinct Elements. CoRR abs/2009.09604 (2020) - [i46]Pasin Manurangsi, Aviad Rubinstein, Tselil Schramm:
The Strongish Planted Clique Hypothesis and Its Consequences. CoRR abs/2011.05555 (2020) - [i45]Jaroslaw Byrka, Szymon Dudycz, Pasin Manurangsi, Jan Marcinkowski, Michal Wlodarczyk:
To Close Is Easier Than To Open: Dual Parameterization To k-Median. CoRR abs/2011.08083 (2020) - [i44]Surbhi Goel, Adam R. Klivans, Pasin Manurangsi, Daniel Reichman:
Tight Hardness Results for Training Depth-2 ReLU Networks. CoRR abs/2011.13550 (2020) - [i43]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen:
Robust and Private Learning of Halfspaces. CoRR abs/2011.14580 (2020) - [i42]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi:
Sample-efficient proper PAC learning with approximate differential privacy. CoRR abs/2012.03893 (2020) - [i41]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
On Avoiding the Union Bound When Answering Multiple Differentially Private Queries. CoRR abs/2012.09116 (2020) - [i40]Andreas Emil Feldmann, Karthik C. S., Euiwoong Lee, Pasin Manurangsi:
A Survey on Approximation in Parameterized Complexity: Hardness and Algorithms. Electron. Colloquium Comput. Complex. TR20 (2020) - 2019
- [i39]Xiaohui Bei, Xinhang Lu, Pasin Manurangsi, Warut Suksompong:
The Price of Fairness for Indivisible Goods. CoRR abs/1905.04910 (2019) - [i38]Piotr Faliszewski, Pasin Manurangsi, Krzysztof Sornat:
Approximation and Hardness of Shift-Bribery. CoRR abs/1908.10562 (2019) - [i37]Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi:
Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin. CoRR abs/1908.11335 (2019) - [i36]Arnab Bhattacharyya, Édouard Bonnet, László Egri, Suprovat Ghoshal, Karthik C. S., Bingkai Lin, Pasin Manurangsi, Dániel Marx:
Parameterized Intractability of Even Set and Shortest Vector Problem. CoRR abs/1909.01986 (2019) - [i35]Badih Ghazi, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker:
Private Aggregation from Fewer Anonymous Messages. CoRR abs/1909.11073 (2019) - [i34]Pasin Manurangsi:
Tight Running Time Lower Bounds for Strong Inapproximability of Maximum k-Coverage, Unique Set Cover and Related Problems (via t-Wise Agreement Testing Theorem). CoRR abs/1910.11850 (2019) - [i33]Arnab Bhattacharyya, Édouard Bonnet, László Egri, Suprovat Ghoshal, Karthik C. S., Bingkai Lin, Pasin Manurangsi, Dániel Marx:
Parameterized Intractability of Even Set and Shortest Vector Problem. Electron. Colloquium Comput. Complex. TR19 (2019) - [i32]Pasin Manurangsi, Akshayaram Srinivasan, Prashant Nalini Vasudevan:
Nearly Optimal Robust Secret Sharing against Rushing Adversaries. IACR Cryptol. ePrint Arch. 2019: 1131 (2019) - 2018
- [i31]Arnab Bhattacharyya, Suprovat Ghoshal, Karthik C. S., Pasin Manurangsi:
Parameterized Intractability of Even Set and Shortest Vector Problem from Gap-ETH. CoRR abs/1803.09717 (2018) - [i30]Anupam Gupta, Euiwoong Lee, Jason Li, Pasin Manurangsi, Michal Wlodarczyk:
Losing Treewidth by Separating Subsets. CoRR abs/1804.01366 (2018) - [i29]Eden Chlamtác, Pasin Manurangsi:
Sherali-Adams Integrality Gaps Matching the Log-Density Threshold. CoRR abs/1804.07842 (2018) - [i28]Irit Dinur, Pasin Manurangsi:
ETH-Hardness of Approximating 2-CSPs and Directed Steiner Network. CoRR abs/1805.03867 (2018) - [i27]Pasin Manurangsi:
A Note on Degree vs Gap of Min-Rep Label Cover and Improved Inapproximability for Connectivity Problems. CoRR abs/1807.00936 (2018) - [i26]Pasin Manurangsi, Luca Trevisan:
Mildly Exponential Time Approximation Algorithms for Vertex Cover, Uniform Sparsest Cut and Related Problems. CoRR abs/1807.09898 (2018) - [i25]Noga Alon, Jonathan D. Cohen, Thomas L. Griffiths, Pasin Manurangsi, Daniel Reichman, Igor Shinkar, Tal Wagner, Alexander Y. Ku:
Multitasking Capacity: Hardness Results and Improved Constructions. CoRR abs/1809.02835 (2018) - [i24]Pasin Manurangsi:
A Note on Max k-Vertex Cover: Faster FPT-AS, Smaller Approximate Kernel and Improved Approximation. CoRR abs/1810.03792 (2018) - [i23]Pasin Manurangsi, Daniel Reichman:
The Computational Complexity of Training ReLU(s). CoRR abs/1810.04207 (2018) - [i22]Pasin Manurangsi, Warut Suksompong:
When Do Envy-Free Allocations Exist? CoRR abs/1811.01630 (2018) - [i21]Karthik C. S., Pasin Manurangsi:
On Closest Pair in Euclidean Metric: Monochromatic is as Hard as Bichromatic. CoRR abs/1812.00901 (2018) - [i20]Arnab Bhattacharyya, Suprovat Ghoshal, Karthik C. S., Pasin Manurangsi:
Parameterized Intractability of Even Set and Shortest Vector Problem from Gap-ETH. Electron. Colloquium Comput. Complex. TR18 (2018) - [i19]Irit Dinur, Pasin Manurangsi:
ETH-Hardness of Approximating 2-CSPs and Directed Steiner Network. Electron. Colloquium Comput. Complex. TR18 (2018) - [i18]Karthik C. S., Pasin Manurangsi:
On Closest Pair in Euclidean Metric: Monochromatic is as Hard as Bichromatic. Electron. Colloquium Comput. Complex. TR18 (2018) - 2017
- [i17]Jeffrey Bosboom, Erik D. Demaine, Martin L. Demaine, Adam Hesterberg, Pasin Manurangsi, Anak Yodpinyanee:
Even 1×n Edge-Matching and Jigsaw Puzzles are Really Hard. CoRR abs/1701.00146 (2017) - [i16]Pasin Manurangsi, Warut Suksompong:
Computing an Approximately Optimal Agreeable Set of Items. CoRR abs/1705.02748 (2017) - [i15]Pasin Manurangsi:
Inapproximability of Maximum Biclique Problems, Minimum $k$-Cut and Densest At-Least-$k$-Subgraph from the Small Set Expansion Hypothesis. CoRR abs/1705.03581 (2017) - [i14]Pasin Manurangsi, Aviad Rubinstein:
Inapproximability of VC Dimension and Littlestone's Dimension. CoRR abs/1705.09517 (2017) - [i13]Pasin Manurangsi, Warut Suksompong:
Asymptotic Existence of Fair Divisions for Groups. CoRR abs/1706.08219 (2017) - [i12]Rajesh Chitnis, Andreas Emil Feldmann, Pasin Manurangsi:
Parameterized Approximation Algorithms for Directed Steiner Network Problems. CoRR abs/1707.06499 (2017) - [i11]Parinya Chalermsook, Marek Cygan, Guy Kortsarz, Bundit Laekhanukit, Pasin Manurangsi, Danupon Nanongkai, Luca Trevisan:
From Gap-ETH to FPT-Inapproximability: Clique, Dominating Set, and More. CoRR abs/1708.04218 (2017) - [i10]Karthik C. S., Bundit Laekhanukit, Pasin Manurangsi:
On the Parameterized Complexity of Approximating Dominating Set. CoRR abs/1711.11029 (2017) - [i9]Karthik C. S., Bundit Laekhanukit, Pasin Manurangsi:
On the Parameterized Complexity of Approximating Dominating Set. Electron. Colloquium Comput. Complex. TR17 (2017) - 2016
- [i8]Pasin Manurangsi, Prasad Raghavendra:
A Birthday Repetition Theorem and Complexity of Approximating Dense CSPs. CoRR abs/1607.02986 (2016) - [i7]Haris Angelidakis, Yury Makarychev, Pasin Manurangsi:
An Improved Integrality Gap for the Calinescu-Karloff-Rabani Relaxation for Multiway Cut. CoRR abs/1611.05530 (2016) - [i6]Pasin Manurangsi:
Almost-Polynomial Ratio ETH-Hardness of Approximating Densest $k$-Subgraph. CoRR abs/1611.05991 (2016) - [i5]Pasin Manurangsi:
Almost-Polynomial Ratio ETH-Hardness of Approximating Densest k-Subgraph. Electron. Colloquium Comput. Complex. TR16 (2016) - 2015
- [i4]Pasin Manurangsi, Dana Moshkovitz:
Approximating Dense Max 2-CSPs. CoRR abs/1507.08348 (2015) - [i3]Pasin Manurangsi, Preetum Nakkiran, Luca Trevisan:
Near-Optimal UGC-hardness of Approximating Max k-CSP_R. CoRR abs/1511.06558 (2015) - [i2]Jeffrey Bosboom, Erik D. Demaine, Martin L. Demaine, Jayson Lynch, Pasin Manurangsi, Mikhail Rudoy, Anak Yodpinyanee:
Dissection with the Fewest Pieces is Hard, Even to Approximate. CoRR abs/1512.06706 (2015) - 2014
- [i1]Pasin Manurangsi, Dana Moshkovitz:
Improved Approximation Algorithms for Projection Games. CoRR abs/1408.4048 (2014)
Coauthor Index
[j24] [j23] [j22] [c87] [c86] [c85] [c84] [c83] [c82] [c81] [c80] [c79] [c78] [c77] [c75] [c74] [c73] [c72] [c71] [c70] [c69] [c68] [c65] [c63] [c61] [c59] [c56] [c55] [c52] [c51] [c50] [c49] [c48] [c42] [c41] [c39] [c38] [c35] [c34] [c33] [c30] [i111] [i108] [i107] [i105] [i103] [i102] [i101] [i100] [i99] [i97] [i96] [i94] [i93] [i92] [i91] [i88] [i86] [i85] [i83] [i82] [i81] [i79] [i78] [i76] [i75] [i74] [i73] [i72] [i71] [i68] [i65] [i63] [i61] [i60] [i56] [i55] [i52] [i49] [i47] [i43] [i42] [i41] [i35]
[j24] [j23] [j22] [c87] [c86] [c85] [c84] [c83] [c82] [c81] [c80] [c79] [c78] [c77] [c75] [c74] [c73] [c72] [c71] [c70] [c69] [c68] [c65] [c63] [c61] [c59] [c56] [c55] [c52] [c51] [c50] [c49] [c48] [c42] [c41] [c39] [c38] [c34] [c33] [c30] [i111] [i108] [i107] [i105] [i103] [i102] [i101] [i100] [i99] [i97] [i96] [i94] [i93] [i92] [i91] [i88] [i86] [i85] [i83] [i82] [i81] [i79] [i78] [i76] [i75] [i74] [i73] [i72] [i71] [i68] [i65] [i63] [i61] [i60] [i56] [i55] [i52] [i49] [i47] [i43] [i42] [i41]
a service of 
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-04-11 20:11 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
