no code implementations • 17 Nov 2022 • Hamed Jalali, Gjergji Kasneci
Ensemble methods aggregate models' predictions by assuming a perfect diversity of local predictors.
no code implementations • 7 Feb 2022 • Hamed Jalali, Gjergji Kasneci
Distributed Gaussian process (DGP) is a popular approach to scale GP to big data which divides the training data into some subsets, performs local inference for each partition, and aggregates the results to acquire global prediction.
1 code implementation • 14 Nov 2021 • Vadim Borisov, Johannes Meier, Johan van den Heuvel, Hamed Jalali, Gjergji Kasneci
Understanding the results of deep neural networks is an essential step towards wider acceptance of deep learning algorithms.
no code implementations • 2 Feb 2021 • Hamed Jalali, Martin Pawelczyk, Gjergji Kasneci
Imposing the \emph{conditional independence assumption} (CI) between the experts renders the aggregation of different expert predictions time efficient at the cost of poor uncertainty quantification.
no code implementations • 17 Oct 2020 • Hamed Jalali, Gjergji Kasneci
The precision matrix encodes conditional dependencies between experts and is used to detect strongly dependent experts and construct an improved aggregation.