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László Egri

Publications and source records attributed to László Egri.

2 recordsLinked to original sources

Parameterized Intractability of Even Set and Shortest Vector Problem

The $k$-Even Set problem is a parameterized variant of the Minimum Distance Problem of linear codes over $\mathbb F_2$, which can be stated as follows: given a generator matrix $\mathbf A$ and an integer $k$, determine whether the code generated by $\mathbf A$ has distance at most $k$, or in other words, whether there is a nonzero vector $\mathbf{x}$ such that $\mathbf A \mathbf{x}$ has at most $k$ nonzero coordinates. The question of whether $k$-Even Set is fixed parameter tractable (FPT) parameterized by the distance $k$ has been repeatedly raised in literature; in fact, it is one of the few remaining open questions from the seminal book of Downey and Fellows (1999). In this work, we show that $k$-Even Set is W[1]-hard under randomized reductions. We also consider the parameterized $k$-Shortest Vector Problem (SVP), in which we are given a lattice whose basis vectors are integral and an integer $k$, and the goal is to determine whether the norm of the shortest vector (in the $\ell_p$ norm for some fixed $p$) is at most $k$. Similar to $k$-Even Set, understanding the complexity of this problem is also a long-standing open question in the field of Parameterized Complexity. We show that, for any $p > 1$, $k$-SVP is W[1]-hard to approximate (under randomized reductions) to some constant factor.

cs.CC↗

Fixed-parameter Approximability of Boolean MinCSPs

The minimum unsatisfiability version of a constraint satisfaction problem (MinCSP) asks for an assignment where the number of unsatisfied constraints is minimum possible, or equivalently, asks for a minimum-size set of constraints whose deletion makes the instance satisfiable. For a finite set $Γ$ of constraints, we denote by MinCSP($Γ$) the restriction of the problem where each constraint is from $Γ$. The polynomial-time solvability and the polynomial-time approximability of MinCSP($Γ$) were fully characterized by Khanna et al. [Siam J. Comput. '00]. Here we study the fixed-parameter (FP-) approximability of the problem: given an instance and an integer $k$, one has to find a solution of size at most $g(k)$ in time $f(k)n^{O(1)}$ if a solution of size at most $k$ exists. We especially focus on the case of constant-factor FP-approximability. We show the following dichotomy: for each finite constraint language $Γ$, either we exhibit a constant-factor FP-approximation for MinCSP($Γ$); or we prove that MinCSP($Γ$) has no constant-factor FP-approximation unless FPT$=$W[1]. In particular, we show that approximating the so-called Nearest Codeword within some constant factor is W[1]-hard. Recently, Arnab et al. [ICALP '18] showed that such a W[1]-hardness of approximation implies that Even Set is W[1]-hard under randomized reductions. Combining our results, we therefore settle the parameterized complexity of Even Set, a famous open question in the field.

cs.CC↗