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Júlia Baligács

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Preprint Aug 2026

Online and Incremental Fractional Vertex Cover on Trees

In this paper we study the fractional vertex cover problem on trees in two related models: online and incremental. In the online model, the vertices of the tree are known a priori and the edges arrive one at a time. The goal is to maintain a fractional vertex cover of the tree, i.e., an assignment of fractional weights from [0,1] to the vertices such that the weights of endpoints of every edge sum up to at least one. After each edge arrival, we need to modify the fractional vertex cover to cover the new edge as well. However, we can only increase the values assigned to vertices. The problem was studied before (in the vertex arrival model) by Wang and Wong, who motivated it as a generalization of the ski-rental problem, but also (more importantly) by its close connection to the dual online matching problem. They presented a 1.901-competitive algorithm for general graphs in the vertex arrival model. We present an $\frac{11}{6} \approx 1.83$-competitive algorithm for trees in the more general edge arrival model. In addition, we study the fractional vertex cover problem in an incremental model, where we again seek a fractional vertex cover after every update, but all the updates to the tree are known to the algorithm a priori. In this model, we give a 1.5-competitive algorithm and provide a matching lower bound.

Júlia Baligács, B. Bosek, Y. Disser et al. · 1 citation
Preprint Jul 2026

A lower bound of 4 for online graph exploration

In the online graph exploration problem, a single agent needs to visit every vertex of an initially unknown graph, which is learned over time in an online fashion, and return to its starting position. We prove that the competitive ratio of this problem is at least 4, improving on the previously best known lower bound of 10/3. A key ingredient of our proof is showing that several restrictions can be imposed on the agent's behavior without affecting the competitive ratio. As a byproduct, we also obtain that certain graph properties, such as the triangle inequality or being subcubic, can be assumed without affecting the competitive ratio.

Júlia Baligács · 0 citations
Preprint Jul 2026

Randomization Helps in Online Graph Exploration: Breaking the Deterministic Lower Bound on Cycles

This work focuses on cycles, a simple graph class which nevertheless captures a key difficulty of online exploration, and develops a randomized algorithm for online exploration of cycles, giving the first provable advantage of randomization in online graph exploration.

Júlia Baligács, Jan Hkazla, Lena Volk · 0 citations