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Documents authored by Kundu, Madhumita

Document
DOI: 10.4230/LIPIcs.MFCS.2025.20
Kernelization in Almost Linear Time for Clustering into Bounded Vertex Cover Components

Authors: Sriram Bhyravarapu, Pritesh Kumar, Madhumita Kundu, Shivesh K. Roy, Sahiba, and Saket Saurabh

Published in: LIPIcs, Volume 345, 50th International Symposium on Mathematical Foundations of Computer Science (MFCS 2025)

Abstract
Motivated by the growing interest in graph clustering and the framework proposed during the Dagstuhl Seminar 23331, we consider a natural specialization of this general approach (as also suggested during the seminar). The seminar introduced a broad perspective on clustering, where the goal is to partition a graph into connected components (or "clusters") that satisfy simple structural integrity constraints - not necessarily limited to cliques. In our work, we focus on the case where each cluster is required to have bounded vertex cover number. Specifically, a connected component C satisfies this condition if there exists a set S ⊆ V(C) with |S| ≤ d such that C - S is an independent set. We study this within the framework of the {Vertex Deletion to d-Vertex Cover Components} ({Vertex Deletion to d-VCC}) problem: given a graph G and an integer k, the task is to determine whether there exists a vertex set S ⊆ V(G) of size at most k such that every connected component of G - S has vertex cover number at most d. We also examine the edge-deletion variant, {Edge Deletion to d-Vertex Cover Components} ({Edge Deletion to d-VCC}), where the goal is to delete at most k edges so that each connected component of the resulting graph has vertex cover number at most d. We obtain following results. 1) {Vertex Deletion to d-VCC} admits a kernel with {𝒪}(d⁶k³) vertices and {𝒪}(d⁹k⁴) edges. 2) {Edge Deletion to d-VCC}, admits a kernel with {𝒪}(d⁴k) vertices and {𝒪}(d⁵k) edges. Both of our kernelization algorithms run in time 𝒪(1.253^d ⋅ (kd)^{𝒪(1)} ⋅ n log n). It is important to note that, unless the Exponential Time Hypothesis (ETH) fails, the dependence on d cannot be improved to 2^{o(d)}, as the case k = 0 reduces to solving the classical Vertex Cover problem, which is known to require 2^{Ω(d)} time under ETH. A key ingredient in our kernelization algorithms is a structural result about the hereditary graph class 𝒢_d, consisting of graphs in which every connected component has vertex cover number at most d. We show that 𝒢_d admits a finite obstruction set (with respect to the induced subgraph relation) of size 2^{𝒪(d²)}, where each obstruction graph has at most 3d + 2 vertices. This combinatorial result may be of independent interest.
Cite as

Sriram Bhyravarapu, Pritesh Kumar, Madhumita Kundu, Shivesh K. Roy, Sahiba, and Saket Saurabh. Kernelization in Almost Linear Time for Clustering into Bounded Vertex Cover Components. In 50th International Symposium on Mathematical Foundations of Computer Science (MFCS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 345, pp. 20:1-20:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{bhyravarapu_et_al:LIPIcs.MFCS.2025.20,
  author =	{Bhyravarapu, Sriram and Kumar, Pritesh and Kundu, Madhumita and Roy, Shivesh K. and Sahiba and Saurabh, Saket},
  title =	{{Kernelization in Almost Linear Time for Clustering into Bounded Vertex Cover Components}},
  booktitle =	{50th International Symposium on Mathematical Foundations of Computer Science (MFCS 2025)},
  pages =	{20:1--20:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-388-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{345},
  editor =	{Gawrychowski, Pawe{\l} and Mazowiecki, Filip and Skrzypczak, Micha{\l}},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2025.20},
  URN =		{urn:nbn:de:0030-drops-241276},
  doi =		{10.4230/LIPIcs.MFCS.2025.20},
  annote =	{Keywords: Parameterized complexity, Polynomial Kernels, Vertex Cover, Finite Forbidden Characterization}
}
Document
DOI: 10.4230/DagRep.14.10.1
New Tools in Parameterized Complexity: Paths, Cuts, and Decomposition (Dagstuhl Seminar 24411)

Authors: Fedor V. Fomin, Dániel Marx, Saket Saurabh, Roohani Sharma, and Madhumita Kundu

Published in: Dagstuhl Reports, Volume 14, Issue 10 (2025)

Abstract
The Dagstuhl Seminar concentrated on the development of new tools arising from the parameterized complexity of cuts, paths, and decompositions in graphs. The last 2 years were very exciting for the area, with a number of breakthroughs. In FOCS 2021, Korhonen introduced a new method for approximating tree decompositions in graphs. His method, which was deeply rooted in classical graph theory, appeared to be a very handy tool for decomposing graphs, and several STOC/FOCS papers developed this method in various settings. In parallel, a novel perspective on graph decompositions was proposed by Bonnet et al. in FOCS 2020. The new theory of twin-width had many exciting consequences, and we were still at the beginning of understanding the real impact of the new decompositions on graph algorithms. In a series of papers (SODA 2021, STOC 2022, SODA 2023), Kim et al. developed beautiful algorithmic methods for handling separators in (undirected, weighted, or directed) graphs by the addition of arcs. The new algorithmic tool was used to resolve a number of long-standing open problems in the area, and it also seemed to pave the road to many more new discoveries. Reis and Rothvoss (Arxiv 2023) announced a ((log n)^{O(n)}) time randomized algorithm to solve integer programs in n variables. This breakthrough had an impact on many problems in parameterized complexity, especially on problems concerning cuts in graphs. Finally, by employing algebraic methods (both new and old), significant progress was made on several problems related to paths, including the classical (k)-disjoint path problems. This seminar brought together people from the parameterized complexity community, specialists in cuts, flows, and connectivity, and those who had been at the forefront of these new developments. In doing so, it consolidated the results achieved in recent years, discussed future research directions, and further explored the potential applications of the methods and techniques described above.
Cite as

Fedor V. Fomin, Dániel Marx, Saket Saurabh, Roohani Sharma, and Madhumita Kundu. New Tools in Parameterized Complexity: Paths, Cuts, and Decomposition (Dagstuhl Seminar 24411). In Dagstuhl Reports, Volume 14, Issue 10, pp. 1-21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{fomin_et_al:DagRep.14.10.1,
  author =	{Fomin, Fedor V. and Marx, D\'{a}niel and Saurabh, Saket and Sharma, Roohani and Kundu, Madhumita},
  title =	{{New Tools in Parameterized Complexity: Paths, Cuts, and Decomposition (Dagstuhl Seminar 24411)}},
  pages =	{1--21},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2025},
  volume =	{14},
  number =	{10},
  editor =	{Fomin, Fedor V. and Marx, D\'{a}niel and Saurabh, Saket and Sharma, Roohani and Kundu, Madhumita},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.10.1},
  URN =		{urn:nbn:de:0030-drops-230258},
  doi =		{10.4230/DagRep.14.10.1},
  annote =	{Keywords: fixed-parameter tractability, intractability, parameterized complexity}
}
Document
DOI: 10.4230/LIPIcs.IPEC.2024.17
Subset Feedback Vertex Set in Tournaments as Fast as Without the Subset

Authors: Satyabrata Jana, Lawqueen Kanesh, Madhumita Kundu, and Saket Saurabh

Published in: LIPIcs, Volume 321, 19th International Symposium on Parameterized and Exact Computation (IPEC 2024)

Abstract
In the Feedback Vertex Set in Tournaments (FVST) problem, we are given a tournament T and a positive integer k. The objective is to determine whether there exists a vertex set X ⊆ V(T) of size at most k such that T-X is a directed acyclic graph. This problem is known to be equivalent to the problem of hitting all directed triangles, thereby using the best-known algorithm for the 3-Hitting Set problem results in an algorithm for FVST with a running time of 2.076^k ⋅ n^{𝒪(1)} [Wahlström, Ph.D. Thesis]. Kumar and Lokshtanov [STACS 2016] designed a more efficient algorithm with a running time of 1.6181^k ⋅ n^{𝒪(1)}. A generalization of FVST, called Subset-FVST, includes an additional subset S ⊆ V(T) in the input. The goal for Subset-FVST is to find a vertex set X ⊆ V(T) of size at most k such that T-X contains no directed cycles that pass through any vertex in S. This generalized problem can also be represented as a 3-Hitting Set problem, leading to a running time of 2.076^k ⋅ n^{𝒪(1)}. Bai and Xiao [Theoretical Computer Science 2023] improved this and obtained an algorithm with running time 2^{k + o(k)} ⋅ n^{𝒪(1)}. In our work, we extend the algorithm of Kumar and Lokshtanov [STACS 2016] to solve Subset-FVST, obtaining an algorithm with a running time {𝒪}(1.6181^k + n^{{𝒪}(1)}), matching the running time for FVST.
Cite as

Satyabrata Jana, Lawqueen Kanesh, Madhumita Kundu, and Saket Saurabh. Subset Feedback Vertex Set in Tournaments as Fast as Without the Subset. In 19th International Symposium on Parameterized and Exact Computation (IPEC 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 321, pp. 17:1-17:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{jana_et_al:LIPIcs.IPEC.2024.17,
  author =	{Jana, Satyabrata and Kanesh, Lawqueen and Kundu, Madhumita and Saurabh, Saket},
  title =	{{Subset Feedback Vertex Set in Tournaments as Fast as Without the Subset}},
  booktitle =	{19th International Symposium on Parameterized and Exact Computation (IPEC 2024)},
  pages =	{17:1--17:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-353-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{321},
  editor =	{Bonnet, \'{E}douard and Rz\k{a}\.{z}ewski, Pawe{\l}},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.IPEC.2024.17},
  URN =		{urn:nbn:de:0030-drops-222438},
  doi =		{10.4230/LIPIcs.IPEC.2024.17},
  annote =	{Keywords: Parameterized algorithms, Feedback vertex set, Tournaments, Fixed parameter tractable, Graph partitions}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2024.64
Exponential-Time Approximation Schemes via Compression

Authors: Tanmay Inamdar, Madhumita Kundu, Pekka Parviainen, M. S. Ramanujan, and Saket Saurabh

Published in: LIPIcs, Volume 287, 15th Innovations in Theoretical Computer Science Conference (ITCS 2024)

Abstract
In this paper, we give a framework to design exponential-time approximation schemes for basic graph partitioning problems such as k-way cut, Multiway Cut, Steiner k-cut and Multicut, where the goal is to minimize the number of edges going across the parts. Our motivation to focus on approximation schemes for these problems comes from the fact that while it is possible to solve them exactly in 2^nn^{{𝒪}(1)} time (note that this is already faster than brute-forcing over all partitions or edge sets), it is not known whether one can do better. Using our framework, we design the first (1+ε)-approximation algorithms for the above problems that run in time 2^{f(ε)n} (for f(ε) < 1) for all these problems. As part of our framework, we present two compression procedures. The first of these is a "lossless" procedure, which is inspired by the seminal randomized contraction algorithm for Global Min-cut of Karger [SODA '93]. Here, we reduce the graph to an equivalent instance where the total number of edges is linearly bounded in the number of edges in an optimal solution of the original instance. Following this, we show how a careful combination of greedy choices and the best exact algorithm for the respective problems can exploit this structure and lead to our approximation schemes. Our first compression procedure bounds the number of edges linearly in the optimal solution, but this could still leave a dense graph as the solution size could be superlinear in the number of vertices. However, for several problems, it is known that they admit significantly faster algorithms on instances where solution size is linear in the number of vertices, in contrast to general instances. Hence, a natural question arises here. Could one reduce the solution size to linear in the number of vertices, at least in the case where we are willing to settle for a near-optimal solution, so that the aforementioned faster algorithms could be exploited? In the second compression procedure, using cut sparsifiers (this time, inspired by Benczúr and Karger [STOC '96]) we introduce "solution linearization" as a methodology to give an approximation-preserving reduction to the regime where solution size is linear in the number of vertices for certain cut problems. Using this, we obtain the first polynomial-space approximation schemes faster than 2^nn^{{𝒪}(1)} for Minimum bisection and Edge Bipartization. Along the way, we also design the first polynomial-space exact algorithms for these problems that run in time faster than 2^nn^{{𝒪}(1)}, in the regime where solution size is linear in the number of vertices. The use of randomized contraction and cut sparsifiers in the exponential-time setting is novel to the best of our knowledge and forms our conceptual contribution.
Cite as

Tanmay Inamdar, Madhumita Kundu, Pekka Parviainen, M. S. Ramanujan, and Saket Saurabh. Exponential-Time Approximation Schemes via Compression. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 287, pp. 64:1-64:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{inamdar_et_al:LIPIcs.ITCS.2024.64,
  author =	{Inamdar, Tanmay and Kundu, Madhumita and Parviainen, Pekka and Ramanujan, M. S. and Saurabh, Saket},
  title =	{{Exponential-Time Approximation Schemes via Compression}},
  booktitle =	{15th Innovations in Theoretical Computer Science Conference (ITCS 2024)},
  pages =	{64:1--64:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-309-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{287},
  editor =	{Guruswami, Venkatesan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2024.64},
  URN =		{urn:nbn:de:0030-drops-195920},
  doi =		{10.4230/LIPIcs.ITCS.2024.64},
  annote =	{Keywords: Exponential-Time Algorithms, Approximation Algorithms, Graph Algorithms, Cut Problems}
}
Document
DOI: 10.4230/LIPIcs.FSTTCS.2023.28
FPT Approximations for Packing and Covering Problems Parameterized by Elimination Distance and Even Less

Authors: Tanmay Inamdar, Lawqueen Kanesh, Madhumita Kundu, M. S. Ramanujan, and Saket Saurabh

Published in: LIPIcs, Volume 284, 43rd IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2023)

Abstract
For numerous graph problems in the realm of parameterized algorithms, using the size of a smallest deletion set (called a modulator) into well-understood graph families as parameterization has led to a long and successful line of research. Recently, however, there has been an extensive study of structural parameters that are potentially much smaller than the modulator size. In particular, recent papers [Jansen et al. STOC 2021; Agrawal et al. SODA 2022] have studied parameterization by the size of the modulator to a graph family ℋ(mod_ℋ(⋅)), elimination distance to ℋ(ed_ℋ(⋅)), and ℋ-treewidth (tw_ℋ(⋅)). These parameters are related by the fact that tw_ℋ lower bounds ed_ℋ, which in turn lower bounds mod_ℋ. While these new parameters have been successfully exploited to design fast exact algorithms their utility (especially that of ed_ℋ and tw_ℋ) in the context of approximation algorithms is mostly unexplored. The conceptual contribution of this paper is to present novel algorithmic meta-theorems that expand the impact of these structural parameters to the area of FPT Approximation, mirroring their utility in the design of exact FPT algorithms. Precisely, we show that if a covering or packing problem is definable in Monadic Second Order Logic and has a property called Finite Integer Index (FII), then the existence of an FPT Approximation Scheme (FPT-AS, i.e., (1±ε)-approximation) parameterized by mod_ℋ(⋅), ed_ℋ(⋅), and tw_ℋ(⋅) is in fact equivalent. As a consequence, we obtain FPT-ASes for a wide range of covering, packing, and domination problems on graphs with respect to these parameters. In the process, we show that several graph problems, that are W[1]-hard parameterized by mod_ℋ, admit FPT-ASes not only when parameterized by mod_ℋ, but even when parameterized by the potentially much smaller parameter tw_ℋ(⋅). In the spirit of [Agrawal et al. SODA 2022], our algorithmic results highlight a broader connection between these parameters in the world of approximation. As concrete exemplifications of our meta-theorems, we obtain FPT-ASes for well-studied graph problems such as Vertex Cover, Feedback Vertex Set, Cycle Packing and Dominating Set, parameterized by tw_ℋ(⋅) (and hence, also by mod_ℋ(⋅) or ed_ℋ(⋅)), where ℋ is any family of minor free graphs.
Cite as

Tanmay Inamdar, Lawqueen Kanesh, Madhumita Kundu, M. S. Ramanujan, and Saket Saurabh. FPT Approximations for Packing and Covering Problems Parameterized by Elimination Distance and Even Less. In 43rd IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 284, pp. 28:1-28:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{inamdar_et_al:LIPIcs.FSTTCS.2023.28,
  author =	{Inamdar, Tanmay and Kanesh, Lawqueen and Kundu, Madhumita and Ramanujan, M. S. and Saurabh, Saket},
  title =	{{FPT Approximations for Packing and Covering Problems Parameterized by Elimination Distance and Even Less}},
  booktitle =	{43rd IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2023)},
  pages =	{28:1--28:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-304-1},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{284},
  editor =	{Bouyer, Patricia and Srinivasan, Srikanth},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2023.28},
  URN =		{urn:nbn:de:0030-drops-194013},
  doi =		{10.4230/LIPIcs.FSTTCS.2023.28},
  annote =	{Keywords: FPT-AS, F-Deletion, Packing, Elimination Distance, Elimination Treewidth}
}
Document
DOI: 10.4230/LIPIcs.MFCS.2023.55
Fixed-Parameter Algorithms for Fair Hitting Set Problems

Authors: Tanmay Inamdar, Lawqueen Kanesh, Madhumita Kundu, Nidhi Purohit, and Saket Saurabh

Published in: LIPIcs, Volume 272, 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023)

Abstract
Selection of a group of representatives satisfying certain fairness constraints, is a commonly occurring scenario. Motivated by this, we initiate a systematic algorithmic study of a fair version of Hitting Set. In the classical Hitting Set problem, the input is a universe 𝒰, a family ℱ of subsets of 𝒰, and a non-negative integer k. The goal is to determine whether there exists a subset S ⊆ 𝒰 of size k that hits (i.e., intersects) every set in ℱ. Inspired by several recent works, we formulate a fair version of this problem, as follows. The input additionally contains a family ℬ of subsets of 𝒰, where each subset in ℬ can be thought of as the group of elements of the same type. We want to find a set S ⊆ 𝒰 of size k that (i) hits all sets of ℱ, and (ii) does not contain too many elements of each type. We call this problem Fair Hitting Set, and chart out its tractability boundary from both classical as well as multivariate perspective. Our results use a multitude of techniques from parameterized complexity including classical to advanced tools, such as, methods of representative sets for matroids, FO model checking, and a generalization of best known kernels for Hitting Set.
Cite as

Tanmay Inamdar, Lawqueen Kanesh, Madhumita Kundu, Nidhi Purohit, and Saket Saurabh. Fixed-Parameter Algorithms for Fair Hitting Set Problems. In 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 272, pp. 55:1-55:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{inamdar_et_al:LIPIcs.MFCS.2023.55,
  author =	{Inamdar, Tanmay and Kanesh, Lawqueen and Kundu, Madhumita and Purohit, Nidhi and Saurabh, Saket},
  title =	{{Fixed-Parameter Algorithms for Fair Hitting Set Problems}},
  booktitle =	{48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023)},
  pages =	{55:1--55:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-292-1},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{272},
  editor =	{Leroux, J\'{e}r\^{o}me and Lombardy, Sylvain and Peleg, David},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2023.55},
  URN =		{urn:nbn:de:0030-drops-185897},
  doi =		{10.4230/LIPIcs.MFCS.2023.55},
  annote =	{Keywords: Fairness, Parameterized Algorithms, Hitting Set}
}
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