806 citations · 1.1k across the 47 of their papers we have counts for
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Full Kullback-Leibler-Divergence Loss for Hyperparameter-free Label Distribution Learning
Maurice Günder, Nico Piatkowski, Christian Bauckhage
The concept of Label Distribution Learning (LDL) is a technique to stabilize classification and regression problems with ambiguous and/or imbalanced labels. A prototypical use-case…
Gradient Flows for L2 Support Vector Machine Training
Christian Bauckhage, Helen Schneider, Benjamin Wulff +1
We explore the merits of training of support vector machines for binary classification by means of solving systems of ordinary differential equations. We thus assume a continuous t…
Informed Pre-Training on Prior Knowledge
Laura von Rueden, Sebastian Houben, Kostadin Cvejoski +2
When training data is scarce, the incorporation of additional prior knowledge can assist the learning process. While it is common to initialize neural networks with weights that ha…
Recurrent Point Review Models
Kostadin Cvejoski, Ramses J. Sanchez, Bogdan Georgiev +2
Deep neural network models represent the state-of-the-art methodologies for natural language processing. Here we build on top of these methodologies to incorporate temporal informa…
Learning Syllogism with Euler Neural-Networks
Tiansi Dong, Chengjiang Li, Christian Bauckhage +3
Traditional neural networks represent everything as a vector, and are able to approximate a subset of logical reasoning to a certain degree. As basic logic relations are better rep…
Recurrent Point Processes for Dynamic Review Models
Kostadin Cvejoski, Ramses J. Sanchez, Bogdan Georgiev +3
Recent progress in recommender system research has shown the importance of including temporal representations to improve interpretability and performance. Here, we incorporate temp…
Neural Conditional Gradients
Patrick Schramowski, Christian Bauckhage, Kristian Kersting
The move from hand-designed to learned optimizers in machine learning has been quite successful for gradient-based and -free optimizers. When facing a constrained problem, however,…
Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants
Mirwaes Wahabzada, Kristian Kersting, Christian Bauckhage +6
Understanding the adaptation process of plants to drought stress is essential in improving management practices, breeding strategies as well as engineering viable crops for a susta…