Zobrazeno 1 - 10
of 389
pro vyhledávání: '"Sunyaev, Ali"'
Autor:
Leiser, Florian, Eckhardt, Sven, Leuthe, Valentin, Knaeble, Merlin, Maedche, Alexander, Schwabe, Gerhard, Sunyaev, Ali
Large language models (LLMs) are prone to hallucinations, i.e., nonsensical, unfaithful, and undesirable text. Users tend to overrely on LLMs and corresponding hallucinations which can lead to misinterpretations and errors. To tackle the problem of o
Externí odkaz:
http://arxiv.org/abs/2403.06710
Publikováno v:
JMIR mHealth and uHealth, Vol 8, Iss 10, p e19280 (2020)
BackgroundNowadays, numerous health-related mobile apps implement gamification in an attempt to draw on the motivational potential of video games and thereby increase user engagement or foster certain health behaviors. However, research on effective
Externí odkaz:
https://doaj.org/article/09c6e50c9bc347dbbcae6381d03817be
Various collaborative distributed machine learning (CDML) systems, including federated learning systems and swarm learning systems, with different key traits were developed to leverage resources for development and use of machine learning (ML) models
Externí odkaz:
http://arxiv.org/abs/2309.16584
The proper design of automated market makers (AMMs) is crucial to enable the continuous trading of assets represented as digital tokens on markets of cryptoeconomic systems. Improperly designed AMMs can make such markets suffer from the thin market p
Externí odkaz:
http://arxiv.org/abs/2309.12818
Autor:
Dehling, Tobias, Sunyaev, Ali
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 establish transparency of information privacy practices (TIPP) so tha
Externí odkaz:
http://arxiv.org/abs/2307.02665
Autor:
Pandl, Konstantin D., Huang, Chun-Yin, Beschastnikh, Ivan, Li, Xiaoxiao, Thiebes, Scott, Sunyaev, Ali
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 distributed (IID). In practice, data is rarely distributed IID. We deve
Externí odkaz:
http://arxiv.org/abs/2305.01657
Federated learning (FL) has received high interest from researchers and practitioners to train machine learning (ML) models for healthcare. Ensuring the trustworthiness of these models is essential. Especially bias, defined as a disparity in the mode
Externí odkaz:
http://arxiv.org/abs/2205.00470
Publikováno v:
JMIR mHealth and uHealth, Vol 3, Iss 1, p e8 (2015)
BackgroundMobile health (mHealth) apps aim at providing seamless access to tailored health information technology and have the potential to alleviate global health burdens. Yet, they bear risks to information security and privacy because users need t
Externí odkaz:
https://doaj.org/article/84f5968fd8e6424aaee36e9599eadcb8
Autor:
Hasebrook, Niklas, Morsbach, Felix, Kannengießer, Niclas, Zöller, Marc, Franke, Jörg, Lindauer, Marius, Hutter, Frank, Sunyaev, Ali
Advanced programmatic hyperparameter optimization (HPO) methods, such as Bayesian optimization, have high sample efficiency in reproducibly finding optimal hyperparameter values of machine learning (ML) models. Yet, ML practitioners often apply less
Externí odkaz:
http://arxiv.org/abs/2203.01717