Fabian Gieseke

Proc. VLDB Endow., 2023

End-to-End Neural Network Training for Hyperbox-Based Classification.

[BibT_eX]

[DOI]

Denis Mayr Lima Martins

Christian Lülf

Marcos Antonio Vaz Salles

CoRR, 2023

BuildSeg: A General Framework for the Segmentation of Buildings.

[BibT_eX]

[DOI]

CoRR, 2023

RapidEarth: A Search-by-Classification Engine for Large-Scale Geospatial Imagery.

[BibT_eX]

[DOI]

Christian Lülf

Denis Mayr Lima Martins

Yongluan Zhou

Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, 2023

Seasonal-Trend Time Series Decomposition on Graphics Processing Units.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV-LiDAR and Machine Learning Methods.

[BibT_eX]

[DOI]

Remote. Sens., 2022

LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing.

[BibT_eX]

[DOI]

CoRR, 2022

Input Selection for Bandwidth-Limited Neural Network Inference.

[BibT_eX]

[DOI]

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Deep learning based 3D point cloud regression for estimating forest biomass.

[BibT_eX]

[DOI]

Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

2021

Attentional Feature Fusion.

[BibT_eX]

[DOI]

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Dataset Sensitive Autotuning of Multi-versioned Code Based on Monotonic Properties - Autotuning in Futhark.

[BibT_eX]

[DOI]

Proceedings of the Trends in Functional Programming - 22nd International Symposium, 2021

Estimating Forest Canopy Height With Multi-Spectral and Multi-Temporal Imagery Using Deep Learning.

[BibT_eX]

[DOI]

Thomas Nyegaard-Signori

Kenneth Grogan

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Implementation of BFASTmonitor Algorithm on Google Earth Engine to Support Large-Area and Sub-Annual Change Monitoring Using Earth Observation Data.

[BibT_eX]

[DOI]

Remote. Sens., 2020

Inferring astrophysical X-ray polarization with deep learning.

[BibT_eX]

[DOI]

CoRR, 2020

Attention as Activation.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Massively-Parallel Change Detection for Satellite Time Series Data with Missing Values.

[BibT_eX]

[DOI]

Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Creating cloud-free satellite imagery from image time series with deep learning.

[BibT_eX]

[DOI]

Tzu-Hsin Karen Chen

Alexander V. Prishchepov

Proceedings of the BIGSPATIAL '20: Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, 2020

Approximate Nearest-Neighbour Fields via Massively-Parallel Propagation-Assisted K-D Trees.

[BibT_eX]

[DOI]

Cosmin Eugen Oancea

Ties Robroek

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Learning Selection Masks for Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Detecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data.

[BibT_eX]

[DOI]

Marcos Antonio Vaz Salles

Christoffer Thrysøe

Andreas Borgstad

Martin Brandt

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Magnitude and Uncertainty Pruning Criterion for Neural Networks.

[BibT_eX]

[DOI]

Vinnie Ko

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Artistic movement recognition by consensus of boosted SVM based experts.

[BibT_eX]

[DOI]

Corneliu Florea

J. Vis. Commun. Image Represent., 2018

Bigger Buffer k-d Trees on Multi-Many-Core Systems.

[BibT_eX]

[DOI]

Proceedings of the High Performance Computing for Computational Science - VECPAR 2018, 2018

Massively-parallel break detection for satellite data.

[BibT_eX]

[DOI]

Proceedings of the 30th International Conference on Scientific and Statistical Database Management, 2018

Training Big Random Forests with Little Resources.

[BibT_eX]

[DOI]

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017

bufferkdtree: A Python library for massive nearest neighbor queries on multi-many-core devices.

[BibT_eX]

[DOI]

Cosmin E. Oancea

Knowl. Based Syst., 2017

Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy.

[BibT_eX]

[DOI]

Jan Kremer

Kristoffer Stensbo-Smidt

Kim Steenstrup Pedersen

IEEE Intell. Syst., 2017

Artistic Movement Recognition by Boosted Fusion of Color Structure and Topographic Description.

[BibT_eX]

[DOI]

Corneliu Florea

Cosmin Toca

Proceedings of the 2017 IEEE Winter Conference on Applications of Computer Vision, 2017

Deep-learnt classification of light curves.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Massively-parallel best subset selection for ordinary least-squares regression.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

2016

Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs.

[BibT_eX]

[DOI]

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Exploring the spectroscopic diversity of type Ia supernovae with Deep Learning and Unsupervised Clustering.

[BibT_eX]

[DOI]

Arlindo M. M. Trindade

Proceedings of the Astroinformatics 2016, Sorrento, Italy, October 19-25, 2016, 2016

2015

Nearest neighbor density ratio estimation for large-scale applications in astronomy.

[BibT_eX]

[DOI]

Jan Kremer

Kim Steenstrup Pedersen

Astron. Comput., 2015

An Efficient Many-Core Implementation for Semi-Supervised Support Vector Machines.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, Optimization, and Big Data, 2015

Batch Steepest-Descent-Mildest-Ascent for Interactive Maximum Margin Clustering.

[BibT_eX]

[DOI]

Tapio Pahikkala

Tom Heskes

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

2014

On Unsupervised Training of Multi-Class Regularized Least-Squares Classifiers.

[BibT_eX]

[DOI]

J. Comput. Sci. Technol., 2014

Fast and simple gradient-based optimization for semi-supervised support vector machines.

[BibT_eX]

[DOI]

Neurocomputing, 2014

A Framework for Data Mining in Wind Power Time Series.

[BibT_eX]

[DOI]

Proceedings of the Data Analytics for Renewable Energy Integration, 2014

Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Speedy greedy feature selection: Better redshift estimation via massive parallelism.

[BibT_eX]

[DOI]

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013

From Supervised to Unsupervised Support Vector Machines and Applications in Astronomy.

[BibT_eX]

[DOI]

Künstliche Intell., 2013

Wind energy prediction and monitoring with neural computation.

[BibT_eX]

[DOI]

Benjamin Satzger

Neurocomputing, 2013

Learning morphological maps of galaxies with unsupervised regression.

[BibT_eX]

[DOI]

Kai Lars Polsterer

Expert Syst. Appl., 2013

On GPU-Based Nearest Neighbor Queries for Large-Scale Photometric Catalogs in Astronomy.

[BibT_eX]

[DOI]

Proceedings of the KI 2013: Advances in Artificial Intelligence, 2013

Towards Non-linear Constraint Estimation for Expensive Optimization.

[BibT_eX]

[DOI]

Proceedings of the Applications of Evolutionary Computation - 16th European Conference, 2013

Support Vector Machines for Wind Energy Prediction in Smart Grids.

[BibT_eX]

[DOI]

Nils André Treiber

Proceedings of the 27th International Conference on Environmental Informatics for Environmental Protection, 2013

Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification.

[BibT_eX]

[DOI]

Tapio Pahikkala

Proceedings of the Asian Conference on Machine Learning, 2013

2012

Resilient <i>k</i>-d trees: <i>k</i>-means in space revisited.

[BibT_eX]

[DOI]

Gabriel Moruz

Jan Vahrenhold

Frontiers Comput. Sci., 2012

Efficient recurrent local search strategies for semi- and unsupervised regularized least-squares classification.

[BibT_eX]

[DOI]

Evol. Intell., 2012

Evolutionary kernel density regression.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2012

Sparse Quasi-Newton Optimization for Semi-supervised Support Vector Machines.

[BibT_eX]

Proceedings of the ICPRAM 2012, 2012

Unsupervised Multi-class Regularized Least-Squares Classification.

[BibT_eX]

[DOI]

Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Von überwachten zu unüberwachten Support-Vektor-Maschinen und Anwendungen in der Astronomie.

[BibT_eX]

[DOI]

Proceedings of the Ausgezeichnete Informatikdissertationen 2012, 2012

2011

From supervised to unsupervised support vector machines and applications in astronomy.

[BibT_eX]

[DOI]

PhD thesis, 2011

Short-Term Wind Energy Forecasting Using Support Vector Regression.

[BibT_eX]

[DOI]

Proceedings of the Soft Computing Models in Industrial and Environmental Applications, 2011

Variance Scaling for EDAs Revisited.

[BibT_eX]

[DOI]

Proceedings of the KI 2011: Advances in Artificial Intelligence, 2011

Speedy Local Search for Semi-Supervised Regularized Least-Squares.

[BibT_eX]

[DOI]

Proceedings of the KI 2011: Advances in Artificial Intelligence, 2011

Analysis of wind energy time series with kernel methods and neural networks.

[BibT_eX]

[DOI]

Proceedings of the Seventh International Conference on Natural Computation, 2011

2010

Pruning spanners and constructing well-separated pair decompositions in the presence of memory hierarchies.

[BibT_eX]

[DOI]

Joachim Gudmundsson

Jan Vahrenhold

J. Discrete Algorithms, 2010

Detecting Quasars in Large-Scale Astronomical Surveys.

[BibT_eX]

[DOI]

Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Resilient K-d Trees: K-Means in Space Revisited.

[BibT_eX]

[DOI]

Gabriel Moruz

Jan Vahrenhold

Proceedings of the ICDM 2010, 2010

2009

Fast evolutionary maximum margin clustering.

[BibT_eX]

[DOI]

Tapio Pahikkala