Thomas Seidl

ORCID

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 125

Top Venues

Ludwig Maximilian University of Munich, Germany (PHD)

Education History

Ludwig Maximilian University of Munich, Germany

PHD

Publications

David Winkel, Niklas Strauß, Matthias Schubert, Thomas Seidl
Simplex Decomposition for Portfolio Allocation Constraints in Reinforcement Learning. CoRR (2024)
Ludwig Zellner, Simon Rauch, Janina Sontheim, Thomas Seidl
On Diverse and Precise Recommendations for Small and Medium-Sized Enterprises. PAKDD (5) (2024)
Valentin Margraf, Marcel Wever, Sandra Gilhuber, Gabriel Marques Tavares, Thomas Seidl, Eyke Hüllermeier
ALPBench: A Benchmark for Active Learning Pipelines on Tabular Data. CoRR (2024)
Michael Fromm, Max Berrendorf, Evgeniy Faerman, Thomas Seidl
Cross-Domain Argument Quality Estimation. ACL (Findings) (2023)
Sandra Gilhuber, Julian Busch, Daniel Rotthues, Christian M. M. Frey, Thomas Seidl
DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification. CoRR (2023)
Sandra Gilhuber, Rasmus Hvingelby, Mang Ling Ada Fok, Thomas Seidl
How to Overcome Confirmation Bias in Semi-Supervised Image Classification by Active Learning. ECML/PKDD (2) (2023)
David Winkel, Niklas Strauß, Matthias Schubert, Yunpu Ma, Thomas Seidl
Constrained Portfolio Management Using Action Space Decomposition for Reinforcement Learning. PAKDD (2) (2023)
Tanveer Hannan, Rajat Koner, Maximilian Bernhard, Suprosanna Shit, Bjoern H. Menze, Volker Tresp, Matthias Schubert, Thomas Seidl
GRAtt-VIS: Gated Residual Attention for Auto Rectifying Video Instance Segmentation. CoRR (2023)
Theresa Ullmann, Anna Beer, Maximilian Hünemörder, Thomas Seidl, Anne-Laure Boulesteix
Over-optimistic evaluation and reporting of novel cluster algorithms: an illustrative study. Adv. Data Anal. Classif. 17 (1) (2023)
Rajat Koner, Tanveer Hannan, Suprosanna Shit, Sahand Sharifzadeh, Matthias Schubert, Thomas Seidl, Volker Tresp
InstanceFormer: An Online Video Instance Segmentation Framework. AAAI (2023)
Andrea Maldonado, Ludwig Zellner, Sven Strickroth, Thomas Seidl
Process Mining Techniques for Collusion Detection in Online Exams. ICPM Workshops (2023)
Tanveer Hannan, Md Mohaiminul Islam, Thomas Seidl, Gedas Bertasius
RGNet: A Unified Retrieval and Grounding Network for Long Videos. CoRR (2023)
David Winkel, Niklas Strauß, Matthias Schubert, Thomas Seidl
Simplex Decomposition for Portfolio Allocation Constraints in Reinforcement Learning. ECAI (2023)
Andrea Maldonado, Gabriel Marques Tavares, Rafael Seidi Oyamada, Paolo Ceravolo, Thomas Seidl
FEEED: Feature Extraction from Event Data. ICPM Doctoral Consortium / Demo (2023)
Sandra Gilhuber, Rasmus Hvingelby, Mang Ling Ada Fok, Thomas Seidl
How To Overcome Confirmation Bias in Semi-Supervised Image Classification By Active Learning. CoRR (2023)
Yao Zhang, Yunpu Ma, Thomas Seidl, Volker Tresp
Adaptive Multi-Resolution Attention with Linear Complexity. IJCNN (2023)
Sandra Gilhuber, Julian Busch, Daniel Rotthues, Christian M. M. Frey, Thomas Seidl
DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification. ECML/PKDD (1) (2023)
Rajat Koner, Tanveer Hannan, Suprosanna Shit, Sahand Sharifzadeh, Matthias Schubert, Thomas Seidl, Volker Tresp
InstanceFormer: An Online Video Instance Segmentation Framework. CoRR (2022)
Michael Fromm, Max Berrendorf, Johanna Reiml, Isabelle Mayerhofer, Siddharth Bhargava, Evgeniy Faerman, Thomas Seidl
Towards a Holistic View on Argument Quality Prediction. CoRR (2022)
Sandra Gilhuber, Philipp Jahn, Yunpu Ma, Thomas Seidl
VERIPS: Verified Pseudo-label Selection for Deep Active Learning. ICDM (2022)
David Winkel, Niklas Strauß, Matthias Schubert, Thomas Seidl
Risk-Aware Reinforcement Learning for Multi-Period Portfolio Selection. ECML/PKDD (6) (2022)
Sandra Gilhuber, Max Berrendorf, Yunpu Ma, Thomas Seidl
Accelerating Diversity Sampling for Deep Active Learning By Low-Dimensional Representations. IAL@PKDD/ECML (2022)
Ellen Hohma, Christian M. m. Frey, Anna Beer, Thomas Seidl
SCAR - Spectral Clustering Accelerated and Robustified. Proc. VLDB Endow. 15 (11) (2022)
Andreas Lohrer, Anna Beer, Maximilian Archimedes Xaver Hünemörder, Jenny Lauterbach, Thomas Seidl, Peer Kröger
AnyCORE - An Anytime Algorithm for Cluster Outlier REmoval. LWDA (2021)
Ludwig Zellner, Janina Sontheim, Florian Richter, Gabriel Lindner, Thomas Seidl
SCORER-Gap: Sequentially Correlated Rules for Event Recommendation Considering Gap Size. ICDM (Workshops) (2021)
Daniyal Kazempour, Johannes Winter, Peer Kröger, Thomas Seidl
On Methods and Measures for the Inspection of Arbitrarily Oriented Subspace Clusters. Datenbank-Spektrum 21 (3) (2021)
Sandra Obermeier, Anna Beer, Florian Wahl, Thomas Seidl
Cluster Flow - an Advanced Concept for Ensemble-Enabling, Interactive Clustering. BTW (2021)
Michael Fromm, Max Berrendorf, Sandra Obermeier, Thomas Seidl, Evgeniy Faerman
Diversity Aware Relevance Learning for Argument Search. ECIR (2) (2021)
Anna Beer, Lisa Stephan, Thomas Seidl
LUCKe - Connecting Clustering and Correlation Clustering. ICDM (Workshops) (2021)
Yao Zhang, Yunpu Ma, Thomas Seidl, Volker Tresp
Adaptive Multi-Resolution Attention with Linear Complexity. CoRR (2021)
Daniyal Kazempour, Anna Beer, Melanie Oelker, Peer Kröger, Thomas Seidl
Compound Segmentation via Clustering on Mol2Vec-based Embeddings. e-Science (2021)
Julian Busch, Anton Kocheturov, Volker Tresp, Thomas Seidl
NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification. CoRR (2021)
Julian Busch, Anton Kocheturov, Volker Tresp, Thomas Seidl
NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification. SSDBM (2021)
Michael Fromm, Evgeniy Faerman, Max Berrendorf, Siddharth Bhargava, Ruoxia Qi, Yao Zhang, Lukas Dennert, Sophia Selle, Yang Mao, Thomas Seidl
Argument Mining Driven Analysis of Peer-Reviews. AAAI (2021)
Anna Wimbauer, Florian Richter, Thomas Seidl
PErrCas: Process Error Cascade Mining in Trace Streams. ICPM Workshops (2021)
Julian Busch, Maximilian Hünemörder, Janis Held, Peer Kröger, Thomas Seidl
Implicit Hough Transform Neural Networks for Subspace Clustering. ICDM (Workshops) (2021)
Anna Beer, Ekaterina Allerborn, Valentin Hartmann, Thomas Seidl
KISS - A fast kNN-based Importance Score for Subspaces. EDBT (2021)
Nataliia Kees, Michael Fromm, Evgeniy Faerman, Thomas Seidl
Active Learning for Argument Strength Estimation. CoRR (2021)
Daniyal Kazempour, Anna Beer, Peer Kröger, Thomas Seidl
I fold you so! An internal evaluation measure for arbitrary oriented subspace clustering. ICDM (Workshops) (2020)
Florian Richter, Janina Sontheim, Ludwig Zellner, Thomas Seidl
TADE: Stochastic Conformance Checking Using Temporal Activity Density Estimation. BPM (2020)
Felix Borutta, Daniyal Kazempour, Felix Mathy, Peer Kröger, Thomas Seidl
Detecting Arbitrarily Oriented Subspace Clusters in Data Streams Using Hough Transform. PAKDD (1) (2020)
Valentyn Melnychuk, Evgeniy Faerman, Ilja Manakov, Thomas Seidl
Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels. CIKM (Workshops) (2020)
Ludwig Zellner, Florian Richter, Janina Sontheim, Andrea Maldonado, Thomas Seidl
Concept Drift Detection on Streaming Data with Dynamic Outlier Aggregation. ICPM Workshops (2020)
Thomas Seidl
Keynote Data Mining on Process Data. ICPM (2020)
Michael Fromm, Max Berrendorf, Sandra Obermeier, Thomas Seidl, Evgeniy Faerman
Diversity Aware Relevance Learning for Argument Search. CoRR (2020)
Andrea Maldonado, Janina Sontheim, Florian Richter, Thomas Seidl
Performance Skyline: Inferring Process Performance Models from Interval Events. ICPM Workshops (2020)
Valentyn Melnychuk, Evgeniy Faerman, Ilja Manakov, Thomas Seidl
Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels. CoRR (2020)
Anna Beer, Dominik Seeholzer, Nadine Sarah Schüler, Thomas Seidl
Angle-Based Clustering. SISAP (2020)
Julian Busch, Jiaxing Pi, Thomas Seidl
PushNet: Efficient and Adaptive Neural Message Passing. CoRR (2020)
Yifeng Lu, Yao Zhang, Florian Richter, Thomas Seidl
k-Nearest Neighbor based Clustering with Shape Alternation Adaptivity. IJCNN (2020)
Daniyal Kazempour, Long Mathias Yan, Peer Kröger, Thomas Seidl
You see a set of wagons - I see one train: Towards a unified view of local and global arbitrarily oriented subspace clusters. ICDM (Workshops) (2020)
Yao Zhang, Yifeng Lu, Thomas Seidl
KNNAC: An Efficient k Nearest Neighbor Based Clustering with Active Core Detection. iiWAS (2020)
Anna Beer, Valentin Hartmann, Thomas Seidl
Orderings of Data - More Than a Tripping Hazard: Visionary. SSDBM (2020)
Julian Busch, Evgeniy Faerman, Matthias Schubert, Thomas Seidl
Learning Self-Expression Metrics for Scalable and Inductive Subspace Clustering. CoRR (2020)
Daniyal Kazempour, Peer Kröger, Thomas Seidl
Towards an Internal Evaluation Measure for Arbitrarily Oriented Subspace Clustering. ICDM (Workshops) (2020)
Julian Busch, Jiaxing Pi, Thomas Seidl
PushNet: Efficient and Adaptive Neural Message Passing. ECAI (2020)
Florian Richter, Yifeng Lu, Daniyal Kazempour, Thomas Seidl
AMTICS: Aligning Micro-clusters to Identify Cluster Structures. DASFAA (1) (2020)
Florian Richter, Yifeng Lu, Daniyal Kazempour, Thomas Seidl
"Show Me the Crowds!" Revealing Cluster Structures Through AMTICS. Data Sci. Eng. 5 (4) (2020)
Florian Richter, Andrea Maldonado, Ludwig Zellner, Thomas Seidl
OTOSO: Online Trace Ordering for Structural Overviews. ICPM Workshops (2020)
Anna Beer, Daniyal Kazempour, Julian Busch, Alexander Tekles, Thomas Seidl
Grace - Limiting the Number of Grid Cells for Clustering High-Dimensional Data. LWDA (2020)
Michael Fromm, Evgeniy Faerman, Max Berrendorf, Siddharth Bhargava, Ruoxia Qi, Yao Zhang, Lukas Dennert, Sophia Selle, Yang Mao, Thomas Seidl
Argument Mining Driven Analysis of Peer-Reviews. CoRR (2020)
Dietrich Trautmann, Michael Fromm, Volker Tresp, Thomas Seidl, Hinrich Schütze
Relational and Fine-Grained Argument Mining. Datenbank-Spektrum 20 (2) (2020)
Max Berrendorf, Evgeniy Faerman, Valentyn Melnychuk, Volker Tresp, Thomas Seidl
Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned. ECIR (2) (2020)
Florian Richter, Yifeng Lu, Ludwig Zellner, Janina Sontheim, Thomas Seidl
TOAD: Trace Ordering for Anomaly Detection. ICPM (2020)
Yifeng Lu, Florian Richter, Thomas Seidl
LSCMiner: Efficient Low Support Closed Itemsets Mining. WISE (2019)
Anna Beer, Daniyal Kazempour, Marcel Baur, Thomas Seidl
Human Learning in Data Science. HCI (34) (2019)
Janis Held, Anna Beer, Thomas Seidl
Chain-detection for DBSCAN. BTW (Workshops) (2019)
Daniyal Kazempour, Lisa Krombholz, Peer Kröger, Thomas Seidl
A Galaxy of Correlations. EDBT (2019)
Florian Richter, Ludwig Zellner, Janina Sontheim, Thomas Seidl
Model-Aware Clustering of Non-conforming Traces. OTM Conferences (2019)
Florian Richter, Florian Wahl, Alona Sydorova, Thomas Seidl
k-process: Model-Conformance-based Clustering of Process Instances. LWDA (2019)
Anna Beer, Daniyal Kazempour, Lisa Stephan, Thomas Seidl
LUCK- Linear Correlation Clustering Using Cluster Algorithms and a kNN based Distance Function. SSDBM (2019)
Florian Richter, Ludwig Zellner, Imen Azaiz, David Winkel, Thomas Seidl
LIProMa: Label-Independent Process Matching. Business Process Management Workshops (2019)
Janina Sontheim, Florian Richter, Thomas Seidl
Temporal Deviations on Event Sequences. LWDA (2019)
Michael Fromm, Evgeniy Faerman, Thomas Seidl
TACAM: Topic And Context Aware Argument Mining. WI (2019)
Daniyal Kazempour, Thomas Seidl
Insights into a running clockwork: On interactive process-aware clustering. EDBT (2019)
Anna Beer, Jennifer Lauterbach, Thomas Seidl
MORe++: k-Means Based Outlier Removal on High-Dimensional Data. SISAP (2019)
Maximilian Archimedes Xaver Hünemörder, Anna Beer, Daniyal Kazempour, Thomas Seidl
CODEC - Detecting Linear Correlations in Dense Clusters using coMAD-based PCA. LWDA (2019)
Daniyal Kazempour, Maksim Kazakov, Peer Kröger, Thomas Seidl
DICE: Density-based Interactive Clustering and Exploration. BTW (2019)
Daniyal Kazempour, Thomas Seidl
On systematic hyperparameter analysis through the example of subspace clustering. SSDBM (2019)
Max Berrendorf, Evgeniy Faerman, Valentyn Melnychuk, Volker Tresp, Thomas Seidl
Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned. CoRR (2019)
Daniyal Kazempour, Anna Beer, Thomas Seidl
Data on RAILs: On Interactive Generation of Artificial Linear Correlated Data. HCI (34) (2019)
Anna Beer, Daniyal Kazempour, Thomas Seidl
Rock - Let the points roam to their clusters themselves. EDBT (2019)
Florian Richter, Thomas Seidl
Looking into the TESSERACT: Time-drifts in event streams using series of evolving rolling averages of completion times. Inf. Syst. 84 (2019)
Anna Beer, Thomas Seidl
Graph Ordering and Clustering: A Circular Approach. SSDBM (2019)
Maximilian Archimedes Xaver Hünemörder, Daniyal Kazempour, Peer Kröger, Thomas Seidl
SIDEKICK: Linear Correlation Clustering with Supervised Background Knowledge. SISAP (2019)
Daniyal Kazempour, Markus Mauder, Peer Kröger, Thomas Seidl
Detecting global hyperparaboloid correlated clusters: a Hough-transform based multicore algorithm. Distributed Parallel Databases 37 (1) (2019)
Daniyal Kazempour, M. A. X. Hünemörder, Thomas Seidl
On coMADs and Principal Component Analysis. SISAP (2019)
Michael Fromm, Evgeniy Faerman, Thomas Seidl
TACAM: Topic And Context Aware Argument Mining. CoRR (2019)
Marwan Hassani, Daniel Töws, Alfredo Cuzzocrea, Thomas Seidl
: an effective and efficient batch-free algorithm for mining sequential patterns over data streams. Int. J. Data Sci. Anal. 8 (3) (2019)
Daniyal Kazempour, Long Mathias Yan, Thomas Seidl
From Covariance to Comode in context of Principal Component Analysis. LWDA (2019)
Anna Beer, Nadine Sarah Schüler, Thomas Seidl
A Generator for Subspace Clusters. LWDA (2019)
Janis Held, Anna Beer, Thomas Seidl
Chain-detection Between Clusters. Datenbank-Spektrum 19 (3) (2019)
Daniyal Kazempour, Anna Beer, Oliver Schrüfer, Thomas Seidl
Clustering Trend Data Time-Series through Segmentation of FFT-decomposed Signal Constituents. LWDA (2019)
Daniyal Kazempour, Kilian Emmerig, Peer Kröger, Thomas Seidl
Detecting Global Periodic Correlated Clusters in Event Series based on Parameter Space Transform. SSDBM (2019)
Daniyal Kazempour, Anna Beer, Friederike Herzog, Daniel Kaltenthaler, Johannes-Y. Lohrer, Thomas Seidl
FATBIRD: A Tool for Flight and Trajectories Analyses of Birds. eScience (2018)
Daniyal Kazempour, Thomas Seidl
Identifying Entangled Data Points on Iteration Trajectories of Clusterings. LWDA (2018)
Daniyal Kazempour, Kevin Bein, Peer Kröger, Thomas Seidl
D-MASC: A Novel Search Strategy for Detecting Regions of Interest in Linear Parameter Space. SISAP (2018)
Yifeng Lu, Thomas Seidl
Towards Efficient Closed Infrequent Itemset Mining Using Bi-Directional Traversing. DSAA (2018)
Daniyal Kazempour, Anna Beer, Johannes-Y. Lohrer, Daniel Kaltenthaler, Thomas Seidl
PARADISO: an interactive approach of parameter selection for the mean shift algorithm. SSDBM (2018)
Göran Kauermann, Thomas Seidl
Data Science: a proposal for a curriculum. Int. J. Data Sci. Anal. 6 (3) (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Thomas Seidl