Publications

Journal papers:

Josif Grabocka, Nicolas Schilling, Lars Schmidt-Thieme (2016):
Latent Time-Series Motifs , ACM Transactions on Knowledge Discovery from Data, TKDD
Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme (2015):
Fast Classification of Univariate and Multivariate Time series Through Shapelets Discovery , Journal of Knowledge and Information Systems, 5-year impact factor 2.02
Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme (2014):
Scalable Classification of Repetitive Time Series Through Frequencies of Local Polynomials , IEEE Transactions on Knowledge and Data Engineering, 5-year impact factor 2.87
Josif Grabocka, Lars Schmidt-Thieme (2014):
Invariant Time-Series Factorization , Journal of Data Mining and Knowledge Discovery, Impact Factor 2.77
Josif Grabocka, Lars Schmidt-Thieme (2014):
Learning Through Non-linearly Supervised Dimensionality Reduction , Springer Transactions on Large-Scale Data- and Knowledge-Centered Systems, LNCS

Peer-reviewed conference papers:

Shayan Jawed, Josif Grabocka, Lars Schmidt-Thieme (2020):
Self-Supervised Learning for Semi-Supervised Time Series Classification, in Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2020).
Rafael Rêgo Drumond, Lukas Brinkmeyer, Josif Grabocka, Lars Schmidt-Thieme (2019):
HIDRA: Head Initialization across Dynamic targets for Robust Architectures, in CoRR abs / 1910.12749 Accepted for publication in the SIAM International Conference on Data Mining (SDM20), 2020
Vijaya Krishna Yalavarthi, Josif Grabocka, Hareesh Mandalapu, Lars Schmidt-Thieme (2019):
Gait verification using deep learning with a pairwise loss, in Accepted in The 18th International Conference of the Biometrics Special Interest Group (BIOSIG 2019).
Ahmed Rashed, Shayan Jawed, Jens Rehberg, Josif Grabocka, Lars Schmidt-Thieme, Andre Hintsches (2019):
A Deep Multi-Task Approach for Residual Value Forecasting, in Accepted In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2019).
Mohsan Jameel, Josif Grabocka, Mofassir ul Islam Arif, Lars Schmidt-Thieme (2019):
Ring-Star: A Sparse Topology for Faster ModelAveraging in Decentralized Parallel SGD, in In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (DMLE @ ECML-PKDD 2019).
Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme (2019):
Attribute-Aware Non-Linear Co-Embeddings of Graph Features, in Accepted in The 13th ACM Recommender Systems Conference (RecSys 2019).
Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme (2019):
Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings, in Accepted in The 25th ACM SIGKDD conference on knowledge discovery and data mining (SIGKDD 2019).
Hadi S. Jomaa, Josif Grabocka, Lars Schmidt-Thieme (2019):
A Hybrid Convolutional Approach for Parking Availability Prediction, in International Conference on Convolutional Neural Networks (IJCNN2019).
Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme (2019):
Multi-Label Network Classification via Weighted Personalized Factorizations, in International Conference on Agents and Artificial Intelligence (ICAART 2019).
Shayan Jawed, Eya Boumaiza, Josif Grabocka, Lars Schmidt-Thieme (2018):
Data-Driven Vehicle Trajectory Forecasting, in Accepted In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases Workshop on (KNOWMe @ ECML PKDD 2018 ).
Hanh TH Nguyen, Martin Wistuba, Josif Grabocka, Lucas Rego Drumond, Lars Schmidt-Thieme (2017):
Personalized Deep Learning for Tag Recommendation, in Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2017), Jeju, South Korea.
With Shah, Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme (2016):
Learning DTW-Shapelets for Time-Series Classification, in ACM IKDD Conference on Data Science. Best Paper Award
Josif Grabocka, Alexandros Dalkalitsis, Athanasios Lois, Evangelos Katsaros, Lars Schmidt-Thieme (2014):
Realistic Optimal Policies for Energy-Efficient Train Driving, in Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems, ITSC 2014.
Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme (2014):
Learning Time-Series Shapelets, in Proceedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2014. Acceptance Rate: 14.6% (151 out of 1036)
Josif Grabocka, Erind Bedalli, Lars Schmidt-Thieme (2014):
Supervised Nonlinear Factorizations Excel In Semi-supervised Regression, in Proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014, Springer, LNCS, Tainan, Taiwan.
Josif Grabocka, Lucas Drumond, Lars Schmidt-Thieme (2013):
Supervised Dimensionality Reduction Via Nonlinear Target Estimation, in Proceedings of the 15th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2013.
Josif Grabocka, Erind Bedalli, Lars Schmidt-Thieme (2012):
Efficient Classification of Long Time Series, in Proceedings of ICT Innovations Conference 2012, Advances in Intelligent Systems and Computing, Volume 207, pp 47-57, Springer, Berlin / Heidelberg.
Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme (2012):
Invariant Time-Series Classification, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'12), Bristol, United Kingdom.
Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme (2012):
Classification of Sparse Time Series via Supervised Matrix Factorization, in Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI'12), Toronto, Canada.