39 citations · 77 across the 14 of their papers we have counts for
14 papers
From Concept to Measurement: A Survey of How the Blockchain Trilemma Is Analyzed
Mansur Masama Aliyu, Niclas Kannengießer, Ali Sunyaev
The blockchain trilemma highlights the difficulty of simultaneously achieving a high degree of decentralization (DoD), scalability, and security in blockchain systems. While numero…
Automated Market Makers: A Stochastic Optimization Approach for Profitable Liquidity Concentration
Simon Caspar Zeller, Paul-Niklas Ken Kandora, Daniel Kirste +3
Concentrated liquidity automated market makers (AMMs), such as Uniswap v3, enable liquidity providers (LPs) to earn liquidity rewards by depositing tokens into liquidity pools. How…
Automated Market Makers: Toward More Profitable Liquidity Provisioning Strategies
Thanos Drossos, Daniel Kirste, Niclas Kannengießer +1
To trade tokens in cryptoeconomic systems, automated market makers (AMMs) typically rely on liquidity providers (LPs) that deposit tokens in exchange for rewards. To profit from su…
Unraveling the Nuances of AI Accountability: A Synthesis of Dimensions Across Disciplines
L. H. Nguyen, S. Lins, M. Renner +1
The widespread diffusion of Artificial Intelligence (AI)-based systems offers many opportunities to contribute to the well-being of individuals and the advancement of economies and…
Collaborative Distributed Machine Learning
David Jin, Niclas Kannengießer, Sascha Rank +1
Various collaborative distributed machine learning (CDML) systems, including federated learning systems and swarm learning systems, with diferent key traits were developed to lever…
Automated Market Makers in Cryptoeconomic Systems: A Taxonomy and Archetypes
Daniel Kirste, Niclas Kannengießer, Ricky Lamberty +1
Designing automated market makers (AMMs) is crucial for decentralized token exchanges in cryptoeconomic systems. At the intersection of software engineering and economics, AMM desi…
A design theory for transparency of information privacy practices
Tobias Dehling, Ali Sunyaev
The rising diffusion of information systems (IS) throughout society poses an increasingly serious threat to privacy as a social value. One approach to alleviating this threat is to…
Scalable Data Point Valuation in Decentralized Learning
Konstantin D. Pandl, Chun-Yin Huang, Ivan Beschastnikh +3
Existing research on data valuation in federated and swarm learning focuses on valuing client contributions and works best when data across clients is independent and identically d…
Reward Systems for Trustworthy Medical Federated Learning
Konstantin D. Pandl, Florian Leiser, Scott Thiebes +1
Federated learning (FL) has received high interest from researchers and practitioners to train machine learning (ML) models for healthcare. Ensuring the trustworthiness of these mo…
Practitioner Motives to Use Different Hyperparameter Optimization Methods
Niclas Kannengießer, Niklas Hasebrook, Felix Morsbach +5
Programmatic hyperparameter optimization (HPO) methods, such as Bayesian optimization and evolutionary algorithms, are highly sample-efficient in identifying optimal hyperparameter…
Architecture Matters: Investigating the Influence of Differential Privacy on Neural Network Design
Felix Morsbach, Tobias Dehling, Ali Sunyaev
One barrier to more widespread adoption of differentially private neural networks is the entailed accuracy loss. To address this issue, the relationship between neural network arch…
Managing Blockchain Systems and Applications: A Process Model for Blockchain Configurations
Olga Labazova, Erol Kazan, Tobias Dehling +2
Blockchain is a radical innovation with a unique value proposition that shifts trust from institutions to algorithms. Still, the potential of blockchains remains elusive due to kno…
On the Convergence of Artificial Intelligence and Distributed Ledger Technology: A Scoping Review and Future Research Agenda
Konstantin D. Pandl, Scott Thiebes, Manuel Schmidt-Kraepelin +1
Developments in Artificial Intelligence (AI) and Distributed Ledger Technology (DLT) currently lead to lively debates in academia and practice. AI processes data to perform tasks t…
Gamification of Enterprise Systems: A Synthesis of Mechanics, Dynamics, and Risks
M. Schmidt-Kraepelin, S. Lins, S. Thiebes +1
Organizations highly depend on enterprise systems (ES), which are unlikely to develop their full potential if end-users neglect system usage. Accordingly, organizations attempt to…