Christian Haas
Zitiert von
Zitiert von
Fairness in machine learning: A survey
S Caton, C Haas
ACM Computing Surveys, 2023
A social compute cloud: Allocating and sharing infrastructure resources via social networks
S Caton, C Haas, K Chard, K Bubendorfer, OF Rana
IEEE Transactions on Services Computing 7 (3), 359-372, 2014
Predicting Amazon spot prices with LSTM networks
M Baughman, C Haas, R Wolski, I Foster, K Chard
Proceedings of the 9th workshop on scientific cloud computing, 1-7, 2018
The Price of Fairness - A Framework to Explore Trade-Offs in Algorithmic Fairness
C Haas
40th International Conference on Information Systems, ICIS 2019, 2019
Fairness metrics and bias mitigation strategies for rating predictions
A Ashokan, C Haas
Information Processing & Management 58 (5), 102646, 2021
Foundations of Trust: Contextualising Trust in Social Clouds
S Caton, C Dukat, T Grenz, C Haas, M Pfadenhauer, C Weinhardt
2nd International Conference on Social Computing and Its Applications, 424-429, 2012
Co-operative infrastructures: An economic model for providing infrastructures for social cloud computing
C Haas, S Caton, K Chard, C Weinhardt
2013 46th Hawaii International Conference on System Sciences, 729-738, 2013
Deconstructing the 2017 changes to AWS spot market pricing
M Baughman, S Caton, C Haas, R Chard, R Wolski, I Foster, K Chard
Proceedings of the 10th Workshop on Scientific Cloud Computing, 19-26, 2019
Finding optimal mentor-mentee matches: A case study in applied two-sided matching
C Haas, M Hall, SL Vlasnik
Heliyon 4 (6), e00634, 2018
Impact of imputation strategies on fairness in machine learning
S Caton, S Malisetty, C Haas
Journal of Artificial Intelligence Research 74, 1011-1035, 2022
Towards self-awareness in cloud markets: A monitoring methodology
I Breskovic, C Haas, S Caton, I Brandic
2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure …, 2011
Engineering incentives in social clouds
C Haas, S Caton, C Weinhardt
Cluster, Cloud and Grid Computing (CCGrid), 2011 11th IEEE/ACM International …, 2011
Algorithmic fairness in AI: an interdisciplinary view
J Pfeiffer, J Gutschow, C Haas, F Möslein, O Maspfuhl, F Borgers, ...
Business & Information Systems Engineering 65 (2), 209-222, 2023
Identification of Multimorbidity Patterns in Rheumatoid Arthritis through Machine Learning
BR England, Y Yang, P Roul, C Haas, L Najjar, H Sayles, F Yu, BC Sauer, ...
Arthritis Care & Research, 2022
Identifying glycemic variability in diabetes patient cohorts and evaluating disease outcomes
MC Nwadiugwu, DR Bastola, C Haas, D Russell
Journal of clinical medicine 10 (7), 1477, 2021
Preference-based resource allocation: using heuristics to solve two-sided matching problems with indifferences
C Haas, SO Kimbrough, S Caton, C Weinhardt
Economics of Grids, Clouds, Systems, and Services: 10th International …, 2013
Towards the gamification of well-being measures
M Hall, SO Kimbrough, C Haas, C Weinhardt, S Caton
2012 IEEE 8th International Conference on E-Science, 1-8, 2012
Incentives and two-sided matching-engineering coordination mechanisms for social clouds
C Haas
KIT Scientific Publishing, 2014
Strategic Learning by e-Service Suppliers in Service Value Networks
C Haas, SO Kimbrough, C van Dinther
Journal of Service Research 16 (3), 259-276, 2013
Fairness in Machine Learning: A Survey.(2020)
S Caton, C Haas
arXiv preprint arXiv:2010.04053, 2010
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