2 citations · 6 across the 11 of their papers we have counts for
6 papers · 1 filter
Plant 'n' Seek: Can You Find the Winning Ticket?
Jonas Fischer, Rebekka Burkholz
The lottery ticket hypothesis has sparked the rapid development of pruning algorithms that aim to reduce the computational costs associated with deep learning during training and m…
Estimating Mutual Information via Geodesic NN
Alexander Marx, Jonas Fischer
Estimating mutual information (MI) between two continuous random variables and allows to capture non-linear dependencies between them, non-parametrically. As such, MI estim…
Lottery Tickets with Nonzero Biases
Jonas Fischer, Advait Gadhikar, Rebekka Burkholz
The strong lottery ticket hypothesis holds the promise that pruning randomly initialized deep neural networks could offer a computationally efficient alternative to deep learning w…
Label-Descriptive Patterns and Their Application to Characterizing Classification Errors
Michael Hedderich, Jonas Fischer, Dietrich Klakow +1
State-of-the-art deep learning methods achieve human-like performance on many tasks, but make errors nevertheless. Characterizing these errors in easily interpretable terms gives i…
Federated Learning from Small Datasets
Michael Kamp, Jonas Fischer, Jilles Vreeken
Federated learning allows multiple parties to collaboratively train a joint model without sharing local data. This enables applications of machine learning in settings of inherentl…
Factoring out prior knowledge from low-dimensional embeddings
Edith Heiter, Jonas Fischer, Jilles Vreeken
Low-dimensional embedding techniques such as tSNE and UMAP allow visualizing high-dimensional data and therewith facilitate the discovery of interesting structure. Although they ar…