Sebastian Buschjäger

Orcid: 0000-0002-2780-3618

According to our database1, Sebastian Buschjäger authored at least 36 papers between 2017 and 2024.

Collaborative distances:

Timeline

2017
2018
2019
2020
2021
2022
2023
2024
0
5
10
5
2
4
5
3
2
6
1
2
2
1
1
1
1

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
MetaQuRe: Meta-learning from Model Quality and Resource Consumption.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Rejection Ensembles with Online Calibration.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

STRATA: Random Forests going Serverless.
Proceedings of the 25th International Middleware Conference, 2024

Language-Based Deployment Optimization for Random Forests (Invited Paper).
Proceedings of the 25th ACM SIGPLAN/SIGBED International Conference on Languages, 2024

Stress-Testing USB Accelerators for Efficient Edge Inference.
Proceedings of the IEEE/ACM Symposium on Edge Computing, 2024

Federated Time Series Classification with ROCKET features.
Proceedings of the 32nd European Symposium on Artificial Neural Networks, 2024

2023
Joint leaf-refinement and ensemble pruning through L<sub>1</sub> regularization.
Data Min. Knowl. Discov., May, 2023

Fast Inference of Tree Ensembles on ARM Devices.
CoRR, 2023

2022
Efficient Realization of Decision Trees for Real-Time Inference.
ACM Trans. Embed. Comput. Syst., November, 2022

Ensemble learning with discrete classifiers on small devices.
PhD thesis, 2022

Reliable Binarized Neural Networks on Unreliable Beyond Von-Neumann Architecture.
IEEE Trans. Circuits Syst. I Regul. Pap., 2022

FeFET-Based Binarized Neural Networks Under Temperature-Dependent Bit Errors.
IEEE Trans. Computers, 2022

Randomized outlier detection with trees.
Int. J. Data Sci. Anal., 2022

Shrub Ensembles for Online Classification.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Monitoring and Feature Extraction.
Proceedings of the Machine Learning under Resource Constraints, 2022

Deep Learning Applications.
Proceedings of the Machine Learning under Resource Constraints, 2022

Cache-Friendly Execution of Tree Ensembles.
Proceedings of the Machine Learning under Resource Constraints - Volume 1: Fundamentals, 2022

Machine Learning Based on Emerging Memories.
Proceedings of the Machine Learning under Resource Constraints - Volume 1: Fundamentals, 2022

Summary Extraction from Streams.
Proceedings of the Machine Learning under Resource Constraints - Volume 1: Fundamentals, 2022

2021
There is no Double-Descent in Random Forests.
CoRR, 2021

Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement.
CoRR, 2021

Providing Meaningful Data Summarizations Using Examplar-based Clustering in Industry 4.0.
CoRR, 2021

Bit Error Tolerance Metrics for Binarized Neural Networks.
CoRR, 2021

GPU-Accelerated Optimizer-Aware Evaluation of Submodular Exemplar Clustering.
CoRR, 2021

Very Fast Streaming Submodular Function Maximization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Margin-Maximization in Binarized Neural Networks for Optimizing Bit Error Tolerance.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

2020
Generalized Negative Correlation Learning for Deep Ensembling.
CoRR, 2020

Very Fast Streaming Submodular Function Maximization.
CoRR, 2020

Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks.
CoRR, 2020

On-Site Gamma-Hadron Separation with Deep Learning on FPGAs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track, 2020

Generalized Isolation Forest: Some Theory and More Applications Extended Abstract.
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

2019
Gaussian Model Trees for Traffic Imputation.
Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods, 2019

2018
Decision Tree and Random Forest Implementations for Fast Filtering of Sensor Data.
IEEE Trans. Circuits Syst. I Regul. Pap., 2018

Big Data Science.
Künstliche Intell., 2018

Realization of Random Forest for Real-Time Evaluation through Tree Framing.
Proceedings of the IEEE International Conference on Data Mining, 2018

2017
Summary Extraction on Data Streams in Embedded Systems.
Proceedings of the Workshop on IoT Large Scale Learning from Data Streams co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), 2017


  Loading...