Approximating Partition in Near-Linear Time
Lin Chen, Jiayi Lian, Yuchen Mao, Guochuan Zhang
2024年份
3被引次数
9顶会引用
摘要
We propose an O(n + 1/ε)-time FPTAS (Fully Polynomial-Time Approximation Scheme) for the classical Partition problem. This is the best possible (up to a polylogarithmic factor) assuming SETH (Strong Exponential Time Hypothesis) [Abboud, Bringmann, Hermelin, and Shabtay'22]. Prior to our work, the best known FPTAS for Partition runs in O(n + 1/ε 5/4 ) time [Deng, Jin and Mao'23, Wu and Chen'22]. Our result is obtained by solving a more general problem of weakly approximating Subset Sum.
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引用它的顶会 Paper9
- An Improved Pseudopolynomial Time Algorithm for Subset SumLin Chen, Jiayi Lian, Yuchen Mao, Guochuan ZhangFOCS 2024 · 被引用 5 次
- A Nearly Quadratic-Time FPTAS for KnapsackLin Chen, Jiayi Lian, Yuchen Mao, Guochuan ZhangSTOC 2024 · 被引用 4 次
- Universe Reduction for APSP: Equivalence of Three Fine-Grained HypothesesNick FischerSTOC 2026 · 被引用 2 次
- Beating Bellman's Algorithm for Subset SumKarl Bringmann, Nick Fischer, Vasileios NakosSODA 2025 · 被引用 2 次
- Long Arithmetic Progressions in Sumsets and Subset Sums: Constructive Proofs and Efficient WitnessesLin Chen, Yuchen Mao, Guochuan ZhangSTOC 2025 · 被引用 1 次
它引用的顶会 Paper11
- On Near-Linear-Time Algorithms for Dense Subset SumKarl Bringmann, Philip WellnitzSODA 2021 · 被引用 19 次
- Top-k-convolution and the quest for near-linear output-sensitive subset sumKarl Bringmann, Vasileios NakosSTOC 2020 · 被引用 18 次
- A Fine-Grained Perspective on Approximating Subset Sum and PartitionKarl Bringmann, Vasileios NakosSODA 2021 · 被引用 14 次
- Approximating Knapsack and Partition via Dense Subset SumsMingyang Deng, Ce Jin, Xiao MaoSODA 2023 · 被引用 10 次
- Faster Algorithms for Bounded Knapsack and Bounded Subset Sum Via Fine-Grained Proximity ResultsLin Chen, Jiayi Lian, Yuchen Mao, Guochuan ZhangSODA 2024 · 被引用 10 次
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