Institution profile

Vrije Universiteit Amsterdam

Academic institutioneurope · nl
Official website
Research library381linked papers
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Selected work

Representative Papers

Optimisation of cyber insurance coverage with selection of cost effective security controls

Feb 01, 2021Computers & security

This study addresses enterprise cybersecurity risk management by jointly optimizing cybersecurity investments (i.e., security control configurations) and cyber insurance decisions (coverage amount and premium) to minimize total risk cost. We propose the first unified optimization framework that simultaneously incorporates insurance strategies and technical security investments, thereby balancing risk transfer and risk reduction. Our methodology integrates integer nonlinear programming, attack graph modeling, Monte Carlo risk simulation, and cost–benefit sensitivity analysis. Evaluated across multiple industry case studies, the model reduces aggregate risk cost by 18–32% and significantly improves the risk-mitigation efficiency per unit security investment. The framework delivers a computationally tractable, empirically verifiable, and quantitatively grounded decision-support tool for strategic cybersecurity resource allocation.

23 citations1 influentialRead paper

Carefree multiple testing with e-processes

Jan 31, 2025

Existing e-BH procedures lack order-invariance over e-processes, causing test conclusions to reverse spuriously upon addition of irrelevant data and failing to control the false discovery rate (FDR) — or even the family-wise error rate (FWER) — under arbitrary dependence. This paper provides the first rigorous proof that e-BH violates FDR control in this setting. Method: We propose a novel, order-invariant multiple testing framework built on e-process upper bounds, featuring a dependence-structure-adaptive calibrator. Contribution/Results: Our method guarantees strict FDR control at level α (i.e., FDR-sup ≤ α) for arbitrary dependence structures among hypotheses. It eliminates temporal instability in rejection sets induced by sequential data arrival, ensuring robustness and reproducibility in dynamic data environments. Theoretical guarantees are established without restrictive assumptions on dependence, and the procedure is computationally tractable.

2 citations1 influentialRead paper

Interpolation in Knowledge Representation

Dec 09, 2025

Craig and uniform interpolation lack theoretical guarantees and are computationally intractable in description logics and logic programming. Method: This paper systematically characterizes the existence boundaries of interpolation for prominent formalisms—including ALC, EL, and Answer Set Programming—by integrating model-theoretic and proof-theoretic criteria; it proposes a theoretically complete, polynomial-time interpolant construction framework. Contribution/Results: We establish the first interpolation property hierarchy across multiple sublogics, develop an extensible interpolant generator, and empirically validate its efficiency and practicality on standard ontologies and rule sets. The approach significantly advances key knowledge engineering tasks, including knowledge forgetting, modular reuse, and explainable reasoning.

2 citationsRead paper

Computational Techniques Enabling the Perception of Virtual Images Exclusive to the Retinal Afterimage

Sep 13, 2022Big Data and Cognitive Computing

How can computational techniques enable perception of virtual images exclusively through retinal afterimages? Method: We propose and implement the first afterimage-specific display method: real-time gaze localization via eye-tracking and visual fixation modeling, coupled with temporally encoded light stimulation to precisely control afterimage generation while strictly isolating the feedforward visual pathway—ensuring image recognition occurs solely within the afterimage. A closed-loop induction–validation experimental system was developed and deployed in real time on AR/VR platforms. Contribution/Results: Participants achieved 92.3% ± 2.1% accuracy in identifying afterimage-specific shapes, demonstrating that afterimages constitute a viable, independent, and controllable information channel. This work establishes retinal afterimages as a programmable visual medium—the first such demonstration—opening new paradigms for neurointerfaces and immersive artistic expression.

2 citationsRead paper

Towards Uniformity and Alignment for Multimodal Representation Learning

Feb 10, 2026

This work addresses the modality gap in multimodal representation learning induced by the InfoNCE objective, which manifests as a conflict between inter-modal alignment and uniformity, as well as intra-modal alignment inconsistencies. The paper proposes the first framework that decouples alignment and uniformity in multimodal learning, employing Hölder divergence–based alignment optimization alongside a dedicated uniformity loss to effectively mitigate these conflicts. Theoretically, the proposed objective is shown to serve as a valid proxy for the global Hölder divergence between multimodal distributions. Notably, the method requires no task-specific components and consistently improves performance across both discriminative tasks (e.g., retrieval) and generative tasks (e.g., UnCLIP), demonstrating its generality and effectiveness.

1 citationsRead paper
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