跳到正文
研踪PaperTrail

论文库

检索计算机领域论文,按研究方向、作者或关键词筛选。

部分采集异常
正在读取账号与研究记录…

全站更新概况

+0新增论文
+0其中 AI 相关
+2已有论文修订
+100新增 AI 导读

arXiv 最近完成扫描:2026-11-15 00:32 · 全站最近入库:2026-11-14 15:09各信源进度 →

统计口径与数据新鲜度

统计 2026-11-14 01:03 — 2026-11-15 01:03(北京时间) · 点击数字查看对应简报;AI 相关包含在新增论文内。

最近完成检查:2026-11-15 00:32最近发现新增版本:2026-11-14 15:09库内论文最新更新时间:2026-11-13 02:59

每分钟刷新已保存的数据。空检查不代表采集异常;新收录可能包含历史论文。AI 导读按新增版本计数。

23,348 已收录论文19,580 AI 相关6,729 有修订112 HF 社区发现

浏览论文库

时间范围跟随排序:版本更新、本站收录或首次发表。最新收录可能包含历史论文。部分信源异常,查看状态 →

找到 2 篇论文 · 按版本更新时间排序上轮扫描起点 2026-11-15 00:30(北京时间)
新论文 · v1arXiv:2611.16573

Tight Cycle-Cover Inequalities and Improved Approximation for Shortest Common Superstring with Reverse Complements

Ryosuke Yamano, Tetsuo Shibuya

原文摘要

The Shortest Common Superstring (SCS) problem is a classical idealized model of genome assembly. However, SCS does not account for the double-stranded nature of DNA: sequencing reads may originate from either strand without a known orientation. This motivates a natural variant, Shortest Common Superstring with Reverse Complements (SCS-RC), which asks for a shortest string containing each input string or its reverse complement as a substring. For SCS, the MGREEDY algorithm constructs an optimal cycle cover of the overlap graph and concatenates the strings obtained by breaking each cycle at its minimum-overlap edge. This algorithm was recently shown to achieve a tight $3$-approximation. Its reverse-complement extension, MGREEDY-RC, also constructs an optimal cycle cover of the overlap graph augmented with reverse complements, but its best known approximation guarantee was $3.75$ (CPM 2026). We extend this cycle-cover inequality to SCS-RC and show that MGREEDY-RC achieves a $3$-approximation, which is tight even over the DNA alphabet. The $3$-approximation guarantee for MGREEDY-RC yields a $2.5$-approximation for TGREEDY-RC, which greedily merges the strings derived from the cycle cover. By replacing this greedy merging step with an algorithm based on a reduction to a maximum-weight Hamiltonian path problem constrained to contain a given perfect matching, we obtain a $(22/9+\varepsilon)$-approximation for every fixed $\varepsilon>0$. This improves upon the previous best ratio of $8/3$ (WABI 2026), establishing the best known polynomial-time approximation guarantee for SCS-RC.

cs.DS

新论文 · v1arXiv:2611.03115

Faster Exact Algorithms for 3- and 4-Coloring: Deterministic Improvements and Further Randomized Speedups

Ryosuke Yamano, Tetsuo Shibuya

原文摘要

We study exact exponential-time algorithms for 3- and 4-coloring. For 3-coloring, the best previously published running-time bound is $O^*(1.3289^n)$, due to Eppstein (SODA 2001). We improve this bound to $O^*(1.3204^n)$ deterministically and $O^*(1.3159^n)$ using randomization. For 4-coloring, the best previously known running-time bound is $O^*(1.7159^n)$, due to Wu, Gu, Jiang, Shao, and Xu (ESA 2024). We improve this bound to $O^*(1.6975^n)$ deterministically and $O^*(1.6933^n)$ using randomization. Our algorithms for both problems combine constraint satisfaction algorithms with dynamic programming over tree and path decompositions, exploiting their complementary strengths on different graph structures. For 6-coloring, the best published randomized running-time bound is exponentially smaller than the best published deterministic bound. For 3- and 4-coloring, however, no such improvement through randomization was previously known. To the best of our knowledge, our results provide the first randomized running-time bounds for these two problems that exponentially improve upon the best previously published deterministic bounds. This raises the question of whether randomization offers an inherent exponential advantage for 3- and 4-coloring.

cs.DS