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Lukáš Folwarczný

Publications and source records attributed to Lukáš Folwarczný.

6 recordsLinked to original sources

Bounds on Functionality and Symmetric Difference -- Two Intriguing Graph Parameters

Functionality ($\mathrm{fun}$) is a graph parameter that generalizes graph degeneracy defined by Alecu et al. [JCTB, 2021]. They research the relation of functionality to many other graphs parameters (tree-width, clique-width, VC-dimension, etc.). Extending their research, we completely characterize the functionality of random graph $G(n,p)$ for all possible $p$. We provide matching (up to a constant factor) lower and upper bound for a large range of $p$. It follows from our bounds for $G(n,p)$, that the maximum functionality (roughly $\sqrt{n}$) is achieved for $p \approx 1/\sqrt{n}$. We complement this by showing that every graph $G$ on $n$ vertices have $\mathrm{fun}(G) \le O(\sqrt{ n \ln n})$ and we give a nearly matching $Ω(\sqrt{n})$-lower bound provided by incident graphs of projective planes. Previously known lower bounds for functionality were only logarithmic in the number of vertices. Further, we study a related graph parameter symmetric difference ($\mathrm{sd}$), the minimum of $|N(u) ~Δ~ N(v)|$ over all pairs of vertices of the ``worst possible'' induced subgraph. It was observed by Alecu et al. that $\mathrm{fun}(G) \le \mathrm{sd}(G)+1$ for every graph $G$. They asked whether the functionality of interval graphs is bounded. Recently, Dallard et al. [RiM, 2024] answered this positively and they constructed an interval graph $G$ with $\mathrm{sd}(G) = Θ(\sqrt[4]{n})$ (even though they did not mention the explicit bound), i.e., they separate the functionality and symmetric difference of interval graphs. We show that $\mathrm{sd}$ of interval graphs is at most $O(\sqrt[3]{n})$ and we provide a different example of an interval graph $G$ with $\mathrm{sd}(G) = Θ(\sqrt[4]{n})$. Further, we show that $\mathrm{sd}$ of circular arc graphs is $Θ(\sqrt{n})$.

math.CO↗

PPP-Completeness and Extremal Combinatorics

Many classical theorems in combinatorics establish the emergence of substructures within sufficiently large collections of objects. Well-known examples are Ramsey's theorem on monochromatic subgraphs and the Erdős-Rado sunflower lemma. Implicit versions of the corresponding total search problems are known to be PWPP-hard; here "implici" means that the collection is represented by a poly-sized circuit inducing an exponentially large number of objects. We show that several other well-known theorems from extremal combinatorics - including Erdős-Ko-Rado, Sperner, and Cayley's formula - give rise to complete problems for PWPP and PPP. This is in contrast to the Ramsey and Erdős-Rado problems, for which establishing inclusion in PWPP has remained elusive. Besides significantly expanding the set of problems that are complete for PWPP and PPP, our work identifies some key properties of combinatorial proofs of existence that can give rise to completeness for these classes. Our completeness results rely on efficient encodings for which finding collisions allows extracting the desired substructure. These encodings are made possible by the tightness of the bounds for the problems at hand (tighter than what is known for Ramsey's theorem and the sunflower lemma). Previous techniques for proving bounds in TFNP invariably made use of structured algorithms. Such algorithms are not known to exist for the theorems considered in this work, as their proofs "from the book" are non-constructive.

cs.CC↗

On Protocols for Monotone Feasible Interpolation

Feasible interpolation is a general technique for proving proof complexity lower bounds. The monotone version of the technique converts, in its basic variant, lower bounds for monotone Boolean circuits separating two NP-sets to proof complexity lower bounds. In a generalized version of the technique, dag-like communication protocols are used instead of monotone Boolean circuits. We study three kinds of protocols and compare their strength. Our results establish the following relationships in the sense of polynomial reducibility: Protocols with equality are at least as strong as protocols with inequality and protocols with equality have the same strength as protocols with a conjunction of two inequalities. Exponential lower bounds for protocols with inequality are known. Obtaining lower bounds for protocols with equality would immediately imply lower bounds for resolution with parities (R(LIN)).

cs.CC↗

Online Algorithms for Multi-Level Aggregation

In the Multi-Level Aggregation Problem (MLAP), requests arrive at the nodes of an edge-weighted tree T, and have to be served eventually. A service is defined as a subtree X of T that contains its root. This subtree X serves all requests that are pending in the nodes of X, and the cost of this service is equal to the total weight of X. Each request also incurs waiting cost between its arrival and service times. The objective is to minimize the total waiting cost of all requests plus the total cost of all service subtrees. MLAP is a generalization of some well-studied optimization problems; for example, for trees of depth 1, MLAP is equivalent to the TCP Acknowledgment Problem, while for trees of depth 2, it is equivalent to the Joint Replenishment Problem. Aggregation problem for trees of arbitrary depth arise in multicasting, sensor networks, communication in organization hierarchies, and in supply-chain management. The instances of MLAP associated with these applications are naturally online, in the sense that aggregation decisions need to be made without information about future requests. Constant-competitive online algorithms are known for MLAP with one or two levels. However, it has been open whether there exist constant competitive online algorithms for trees of depth more than 2. Addressing this open problem, we give the first constant competitive online algorithm for networks of arbitrary (fixed) number of levels. The competitive ratio is O(D^4 2^D), where D is the depth of T. The algorithm works for arbitrary waiting cost functions, including the variant with deadlines. We also show several additional lower and upper bound results for some special cases of MLAP, including the Single-Phase variant and the case when the tree is a path.

cs.DS↗

IV-matching is strongly NP-hard

IV-matching is a generalization of perfect bipartite matching. The complexity of finding IV-matching in a graph was posted as an open problem at the ICALP 2014 conference. In this note, we resolve the question and prove that, contrary to the expectations of the authors, the given problem is strongly NP-hard (already in the simplest non-trivial case of four layers). Hence it is unlikely that there would be an efficient (polynomial or pseudo-polynomial) algorithm solving the problem.

cs.DM↗

General Caching Is Hard: Even with Small Pages

Caching (also known as paging) is a classical problem concerning page replacement policies in two-level memory systems. General caching is the variant with pages of different sizes and fault costs. We give the first NP-hardness result for general caching with small pages: General caching is (strongly) NP-hard even when page sizes are limited to {1, 2, 3}. It holds already in the fault model (each page has unit fault cost) as well as in the bit model (each page has the same fault cost as size). We also give a very short proof of the strong NP-hardness of general caching with page sizes restricted to {1, 2, 3} and arbitrary costs.

cs.CC↗