Search Results for author: János Kertész

Found 14 papers, 7 papers with code

A Comparative Analysis of Wealth Index Predictions in Africa between three Multi-Source Inference Models

1 code implementation3 Aug 2024 Márton Karsai, János Kertész, Lisette Espín-Noboa

Here, we compare the Relative Wealth Index (RWI) inferred by Chi et al. (2022) with the International Wealth Index (IWI) inferred by Lee and Braithwaite (2022) and Esp\'in-Noboa et al. (2023) across six Sub-Saharan African countries.

Robustness of Decentralised Learning to Nodes and Data Disruption

no code implementations3 May 2024 Luigi Palmieri, Chiara Boldrini, Lorenzo Valerio, Andrea Passarella, Marco Conti, János Kertész

Through these configurations, we are able to show the non-trivial interplay between the properties of the network connecting nodes, the persistence of knowledge acquired collectively before disruption or lack thereof, and the effect of data availability pre- and post-disruption.

Milgram's experiment in the knowledge space: Individual navigation strategies

no code implementations9 Apr 2024 Manran Zhu, János Kertész

Data deluge characteristic for our times has led to information overload, posing a significant challenge to effectively finding our way through the digital landscape.

Graph Embedding Navigate

Initialisation and Topology Effects in Decentralised Federated Learning

1 code implementation23 Mar 2024 Arash Badie-Modiri, Chiara Boldrini, Lorenzo Valerio, János Kertész, Márton Karsai

Fully decentralised federated learning enables collaborative training of individual machine learning models on distributed devices on a communication network while keeping the training data localised.

Federated Learning

Coordination-free Decentralised Federated Learning on Complex Networks: Overcoming Heterogeneity

no code implementations7 Dec 2023 Lorenzo Valerio, Chiara Boldrini, Andrea Passarella, János Kertész, Márton Karsai, Gerardo Iñiguez

Federated Learning (FL) is a well-known framework for successfully performing a learning task in an edge computing scenario where the devices involved have limited resources and incomplete data representation.

Edge-computing Federated Learning

Estimating the loss of economic predictability from aggregating firm-level production networks

no code implementations22 Feb 2023 Christian Diem, András Borsos, Tobias Reisch, János Kertész, Stefan Thurner

Using a nearly complete nationwide FPN, containing 243, 399 Hungarian firms with 1, 104, 141 supplier-buyer-relations we self-consistently compare production losses on the aggregated industry-level production network (IPN) and the granular FPN.

Interpreting wealth distribution via poverty map inference using multimodal data

1 code implementation17 Feb 2023 Lisette Espín-Noboa, János Kertész, Márton Karsai

Here, we propose a pipeline of machine learning models to infer the mean and standard deviation of wealth across multiple geographically clustered populated places, and illustrate their performance in Sierra Leone and Uganda.

Quantifying firm-level economic systemic risk from nation-wide supply networks

no code implementations15 Apr 2021 Christian Diem, András Borsos, Tobias Reisch, János Kertész, Stefan Thurner

While knowing the impact of individual companies on national economies is a prerequisite for efficient risk management, the quantitative assessment of the involved economic systemic risks (ESR) is hitherto practically non-existent, mainly because of a lack of fine-grained data in combination with coherent methods.

Management

Stability of Imbalanced Triangles in Gene Regulatory Networks of Cancerous and Normal Cells

no code implementations7 Oct 2020 Abbas Karimi Rizi, Mina Zamani, Amirhossein Shirazi, G. Reza Jafari, János Kertész

Here we focus on a particular of motifs in the GRN, the triangles, which are imbalanced if the number of negative interactions are odd.

Attention dynamics on the Chinese social media Sina Weibo during the COVID-19 pandemic

1 code implementation10 Aug 2020 Hao Cui, János Kertész

We study the real-time Hot Search List (HSL), which provides the ranking of the most popular 50 hashtags based on the amount of Sina Weibo searches.

Physics and Society Social and Information Networks

Sampling networks by nodal attributes

1 code implementation13 Feb 2019 Yohsuke Murase, Hang-Hyun Jo, János Török, János Kertész, Kimmo Kaski

Assuming that the nodal attributes are independently drawn from an arbitrary distribution $\rho(h)$ and that the sampling probability $r(h_i , h_j)$ for a link $ij$ of nodal attributes $h_i$ and $h_j$ is also arbitrary, we are able to derive exact analytic expressions of the sampled network for such network characteristics as the degree distribution, degree correlation, and clustering spectrum.

Physics and Society Social and Information Networks

What does Big Data tell? Sampling the social network by communication channels

1 code implementation27 Nov 2015 János Török, Yohsuke Murase, Hang-Hyun Jo, János Kertész, Kimmo Kaski

For example, while it is expected that the degree distribution of the whole social network has a maximum at a value larger than one, we get a monotonously decreasing distribution as observed in empirical studies of single channel data.

Physics and Society Social and Information Networks

The most controversial topics in Wikipedia: A multilingual and geographical analysis

no code implementations23 May 2013 Taha Yasseri, Anselm Spoerri, Mark Graham, János Kertész

We present, visualize and analyse the similarities and differences between the controversial topics related to "edit wars" identified in 10 different language versions of Wikipedia.

Edit wars in Wikipedia

1 code implementation19 Jul 2011 Róbert Sumi, Taha Yasseri, András Rung, András Kornai, János Kertész

We present a new, efficient method for automatically detecting severe conflicts `edit wars' in Wikipedia and evaluate this method on six different language WPs.

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