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        <identifier>oai:drops-oai.dagstuhl.de:27396</identifier>
        <datestamp>2026-08-21T14:42:38Z</datestamp>
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          <dc:title>Bi-Criteria Approximations for Vertex Deletion Problems and d-Hitting Set</dc:title>
          <dc:creator>Mandal, Soumen</dc:creator>
          <dc:creator>Rai, Ashutosh</dc:creator>
          <dc:creator>Saurabh, Saket</dc:creator>
          <dc:subject>Parameterized approximation algorithms</dc:subject>
          <dc:subject>bi-criteria approximation</dc:subject>
          <dc:subject>vertex deletion problems</dc:subject>
          <dc:subject>d-Hitting Set</dc:subject>
          <dc:subject>branching algorithms</dc:subject>
          <dc:subject>sampling step</dc:subject>
          <dc:description>We study bi-criteria approximation algorithms for vertex deletion problems in the (k,W) setting, where both the solution size and total weight are bounded simultaneously. Given a graph G, a weight function w:V → ℚ^+, a size bound k, and a weight budget W, a bi-criteria (a,b)-approximation algorithm either certifies that no solution of size at most k and weight at most W exists, or returns a solution of size at most ak and weight at most bW. Parameterizing by the solution size k - rather than the weight budget W - allows our algorithms to handle arbitrary positive rational weights without any lower bound assumption, addressing a fundamental limitation of prior W-parameterized approaches.&#13;
We obtain two families of results. For general vertex deletion problems Π-Deletion admitting a polynomial-time weighted α-approximation, we obtain a polynomial-time (α(λ+1),α(1+1/(λ)))-approximation for any λ &gt; 0, a randomized FPT improvement for problems admitting a sampling step, and a deterministic FPT version for problems with bounded obstruction size. For (k,W)-d-Hitting Set, which captures vertex deletion problems with obstruction size at most d, we design a polynomial-time (d,d)-approximation, a parameterized family of ((1-ε)d, d)-approximations improving the size factor below d, and two algorithms that simultaneously push both factors below d: a ((d+1)/2,(d+1)/2)-approximation and a more refined (d-γ,d-γ)-approximation for any γ ∈ (0,(d-1)/2). All algorithms work with arbitrary positive rational weights and are parameterized by the solution size k.&#13;
To demonstrate the broad applicability of our framework, we instantiate our results on six well-studied vertex deletion problems: Cluster Vertex Deletion, FVS in Tournaments, Split Vertex Deletion, Feedback Vertex Set, d-Path Vertex Cover, and Pathwidth-One Vertex Deletion. In fact, our general results apply to any vertex deletion problem admitting a polynomial-time weighted approximation algorithm, and the six problems serve as representative examples spanning a range of obstruction structures - from bounded-size obstructions to unbounded ones. For (k,W) setting of Feedback Vertex Set and Pathwidth-One Vertex Deletion, we establish new sampling steps enabling the FPT approximation results. For Pathwidth-One Vertex Deletion, we additionally prove a polynomial-time 3-approximation for the weighted version on general graphs.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Soumen Mandal and Ashutosh Rai and Saket Saurabh</dc:contributor>
          <dc:date>2026</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 386, 51st International Symposium on Mathematical Foundations of Computer Science (MFCS 2026)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.MFCS.2026.15</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-273963</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2026.15</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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