3 citations · 8 across the 6 of their papers we have counts for
8 papers
Diagnosing Temporal Misalignment in Multichannel Time-Series Classification with Minimum Description Length
Sebastian Buschjäger, Michael Frichert, Daniel Kuhse +2
Multichannel time-series classification commonly assumes synchronized sensor streams, although latency, clock drift, and preprocessing can introduce relative delays during data col…
You Only Look Once at Anytime (AnytimeYOLO): Analysis and Optimization of Early-Exits for Object-Detection
Daniel Kuhse, Harun Teper, Sebastian Buschjäger +2
We introduce AnytimeYOLO, a family of variants of the YOLO architecture that enables anytime object detection. Our AnytimeYOLO networks allow for interruptible inference, i.e., the…
Fast Inference of Tree Ensembles on ARM Devices
Simon Koschel, Sebastian Buschjäger, Claudio Lucchese +1
With the ongoing integration of Machine Learning models into everyday life, e.g. in the form of the Internet of Things (IoT), the evaluation of learned models becomes more and more…
There is no Double-Descent in Random Forests
Sebastian Buschjäger, Katharina Morik
Random Forests (RFs) are among the state-of-the-art in machine learning and offer excellent performance with nearly zero parameter tuning. Remarkably, RFs seem to be impervious to…
Providing Meaningful Data Summarizations Using Exemplar-based Clustering in Industry 4.0
Philipp-Jan Honysz, Alexander Schulze-Struchtrup, Sebastian Buschjäger +1
Data summarizations are a valuable tool to derive knowledge from large data streams and have proven their usefulness in a great number of applications. Summaries can be found by op…
Bit Error Tolerance Metrics for Binarized Neural Networks
Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen +5
To reduce the resource demand of neural network (NN) inference systems, it has been proposed to use approximate memory, in which the supply voltage and the timing parameters are tu…
Very Fast Streaming Submodular Function Maximization
Sebastian Buschjäger, Philipp-Jan Honysz, Lukas Pfahler +1
Data summarization has become a valuable tool in understanding even terabytes of data. Due to their compelling theoretical properties, submodular functions have been in the focus o…
Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks
Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen +6
Non-volatile memory, such as resistive RAM (RRAM), is an emerging energy-efficient storage, especially for low-power machine learning models on the edge. It is reported, however, t…