3 citations · 5 across the 20 of their papers we have counts for
22 papers
Decisive Margins in Differentially Private Voting
Quentin Hillebrand, Pasin Manurangsi, Vorapong Suppakitpaisarn +1
Differential privacy protects individual voting records by injecting randomness into the published outcome, but this noise can lead to erroneous results when an election is close.…
Publishing Below-Threshold Triangle Counts under Local Weight Differential Privacy
Kevin Pfisterer, Quentin Hillebrand, Vorapong Suppakitpaisarn
We propose an algorithm for counting below-threshold triangles in weighted graphs under local weight differential privacy. While prior work has largely focused on unweighted graphs…
Approximation Algorithms for the -Matching and List-Restricted Variants of MaxQAP
Jiratchaphat Nanta, Vorapong Suppakitpaisarn, Piyashat Sripratak
We study approximation algorithms for two natural generalizations of the Maximum Quadratic Assignment Problem (MaxQAP). In the Maximum List-Restricted Quadratic Assignment Problem,…
Improved Differentially Private Algorithms for Rank Aggregation
Quentin Hillebrand, Pasin Manurangsi, Vorapong Suppakitpaisarn +1
Rank aggregation is a task of combining the rankings of items from multiple users into a single ranking that best represents the users' rankings. Alabi et al. (AAAI'22) presents di…
Optimal Representation for Right-to-Left Parallel Scalar Point Multiplication
Kittiphon Phalakarn, Kittiphop Phalakarn, Vorapong Suppakitpaisarn
This paper introduces an optimal representation for a right-to-left parallel elliptic curve scalar point multiplication. The right-to-left approach is easier to parallelize than th…
Communication-Efficient Publication of Sparse Vectors under Differential Privacy
Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya
In this work, we propose a differentially private algorithm for publishing matrices aggregated from sparse vectors. These matrices include social network adjacency matrices, user-i…
Facility Location Problem under Local Differential Privacy without Super-set Assumption
Kevin Pfisterer, Quentin Hillebrand, Vorapong Suppakitpaisarn
In this paper, we introduce an adaptation of the facility location problem and analyze it within the framework of local differential privacy (LDP). Under this model, we ensure the…
Counting Graphlets of Size under Local Differential Privacy
Vorapong Suppakitpaisarn, Donlapark Ponnoprat, Nicha Hirankarn +1
The problem of counting subgraphs or graphlets under local differential privacy is an important challenge that has attracted significant attention from researchers. However, much o…
Locally Differentially Private Graph Clustering via the Power Iteration Method
Vorapong Suppakitpaisarn, Sayan Mukherjee
We propose a locally differentially private graph clustering algorithm. Previous works have explored this problem, including approaches that apply spectral clustering to graphs gen…
Cycle Counting under Local Differential Privacy for Degeneracy-bounded Graphs
Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya
We propose an algorithm for counting the number of cycles under local differential privacy for degeneracy-bounded input graphs. Numerous studies have focused on counting the number…
Minsum Problem for Discrete and Weighted Set Flow on Dynamic Path Network
Bubai Manna, Bodhayan Roy, Vorapong Suppakitpaisarn
In this research, we examine the minsum flow problem in dynamic path networks where flows are represented as discrete and weighted sets. The minsum flow problem has been widely stu…
On Approximating the Dynamic and Discrete Network Flow Problem
Bubai Manna, Bodhayan Roy, Vorapong Suppakitpaisarn
We examine the dynamic network flow problem under the assumption that the flow consists of discrete units. The dynamic network flow problem is commonly addressed in the context of…
Utilizing Graph Sparsification for Pre-processing in Maxcut QUBO Solver
Vorapong Suppakitpaisarn, Jin-Kao Hao
We suggest employing graph sparsification as a pre-processing step for maxcut programs using the QUBO solver. Quantum(-inspired) algorithms are recognized for their potential effic…
Communication Cost Reduction for Subgraph Counting under Local Differential Privacy via Hash Functions
Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya
We suggest the use of hash functions to cut down the communication costs when counting subgraphs under edge local differential privacy. While various algorithms exist for computing…
Local Differential Privacy for Number of Paths and Katz Centrality
Louis Betzer, Vorapong Suppakitpaisarn, Quentin Hillebrand
In this paper, we give an algorithm to publish the number of paths and Katz centrality under the local differential privacy (LDP), providing a thorough theoretical analysis. Althou…
Local Differential Privacy-Preserving Spectral Clustering for General Graphs
Sayan Mukherjee, Vorapong Suppakitpaisarn
Spectral clustering is a widely used algorithm to find clusters in networks. Several researchers have studied the stability of spectral clustering under local differential privacy…
Efficient Additions and Montgomery Reductions of Large Integers for SIMD
Pengchang Ren, Reiji Suda, Vorapong Suppakitpaisarn
This paper presents efficient algorithms, designed to leverage SIMD for performing Montgomery reductions and additions on integers larger than 512 bits. The existing algorithms enc…
Performances of Symmetric Loss for Private Data from Exponential Mechanism
Jing Bi, Vorapong Suppakitpaisarn
This study explores the robustness of learning by symmetric loss on private data. Specifically, we leverage exponential mechanism (EM) on private labels. First, we theoretically re…
Worst-Case Analysis of LPT Scheduling on Small Number of Non-Identical Processors
Takuto Mitsunobu, Reiji Suda, Vorapong Suppakitpaisarn
The approximation ratio of the longest processing time (LPT) scheduling algorithm has been studied in several papers. While the tight approximation ratio is known for the case when…
Tight Lower Bound for Average Number of Terms in Optimal Double-base Number System
Vorapong Suppakitpaisarn
We show in this note that the average number of terms in the optimal double-base number system is in Omega(n / log n). The lower bound matches the upper bound shown earlier by Dimi…
On the Size of Minimal Separators for Treedepth Decomposition
Zijian Xu, Vorapong Suppakitpaisarn
Treedepth decomposition has several practical applications and can be used to speed up many parameterized algorithms. There are several works aiming to design a scalable algorithm…
On the minimal Hamming weight of a multi-base representation
Daniel Krenn, Vorapong Suppakitpaisarn, Stephan Wagner
Given a finite set of bases , , \dots, (integers greater than ), a multi-base representation of an integer~ is a sum with summands $db_1^{α_1}b_2^{α_2} \cdots…