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Masaryk University

Academic institutioneurope · cz
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Research library127linked papers
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Selected work

Representative Papers

Efficient reversal of transductions of sparse graph classes

Jan 21, 2026

This work investigates the efficient approximate inversion of first-order definable graph transductions where the source graphs belong to sparse classes. For graph classes with structurally bounded expansion, we design an O(n⁴)-time algorithm that, given an input graph G, reconstructs a vertex-colored graph H of bounded expansion such that G can be recovered from H via a first-order interpretation. Our result resolves an open problem posed by Gajarský et al., significantly weakening the required conditions for invertible transductions to merely unary stability and inherent linear neighborhood complexity. As a consequence, we obtain a novel equivalent characterization of structurally bounded expansion classes, thereby establishing a deep connection between structural graph properties and logical definability.

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Computing Patient Similarity Based on Unstructured Clinical Notes

Jan 12, 2026International Conference on Text, Speech and Dialogue

This work proposes a novel method for computing multidimensional patient similarity from unstructured clinical text to support precision medicine. For each patient, all clinical notes are first embedded and aggregated into a matrix, from which a low-rank latent representation is learned to capture shared patterns across dimensions such as clinical history, treatment regimens, and adverse events. By modeling the entirety of clinical notes as a matrix and leveraging low-rank representations for similarity analysis, this approach overcomes the limitations of traditional methods that rely on structured data or keyword matching. Experiments on data from 4,267 breast cancer patients demonstrate that the proposed method effectively supports downstream tasks including personalized treatment recommendation and toxicity risk prediction.

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