Thomas Seidl 0001
71 publications
15 venues
H Index 24
Affiliation
Ludwig Maximilians University of Munich, Institute for Computer Science, GermanyRWTH Aachen University, Germany
Links
DBLPGoogle Scholar
ORCID- https://www.dbs.ifi.lmu.de/cms/Thomas_Seidl/
- http://www-i9.informatik.rwth-aachen.de/Team/seidl/
- https://dl.acm.org/profile/81100145971
- https://mathgenealogy.org/id.php?id=18471
- https://www.wikidata.org/entity/Q102169557
- https://mathscinet.ams.org/mathscinet/MRAuthorID/922698
- https://d-nb.info/gnd/12009486X
| Name | Venue | Year | citations |
|---|---|---|---|
InstanceFormer: An Online Video Instance Segmentation Framework.
|
AAAI | 2023 | 0 |
| Adaptive Multi-Resolution Attention with Linear Complexity.
|
IJCNN | 2023 | 0 |
| How to Overcome Confirmation Bias in Semi-Supervised Image Classification by Active Learning.
|
ECML/PKDD | 2023 | 0 |
| DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification.
|
ECML/PKDD | 2023 | 0 |
| Constrained Portfolio Management Using Action Space Decomposition for Reinforcement Learning.
|
PAKDD | 2023 | 0 |
| Simplex Decomposition for Portfolio Allocation Constraints in Reinforcement Learning.
|
ECAI | 2023 | 0 |
| Risk-Aware Reinforcement Learning for Multi-Period Portfolio Selection.
|
ECML/PKDD | 2022 | 0 |
| VERIPS: Verified Pseudo-label Selection for Deep Active Learning.
|
ICDM | 2022 | 0 |
| Argument Mining Driven Analysis of Peer-Reviews.
|
AAAI | 2021 | 0 |
| Diversity Aware Relevance Learning for Argument Search.
|
ECIR | 2021 | 0 |
| k-Nearest Neighbor based Clustering with Shape Alternation Adaptivity.
|
IJCNN | 2020 | 1 |
| PushNet: Efficient and Adaptive Neural Message Passing.
|
ECAI | 2020 | 10 |
| Detecting Arbitrarily Oriented Subspace Clusters in Data Streams Using Hough Transform.
|
PAKDD | 2020 | 0 |
| Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned.
|
ECIR | 2020 | 0 |
| Human Learning in Data Science.
|
HCI | 2019 | 0 |
| Data on RAILs: On Interactive Generation of Artificial Linear Correlated Data.
|
HCI | 2019 | 1 |
| Infusing Geo-Recency Mixture Models for Effective Location Prediction in LBSN.
|
SDM | 2016 | 5 |
| Effect of Heuristics on Serendipity in Path-Based Storytelling with Linked Data.
|
HCI | 2016 | 6 |
| Normalized Semantic Web Distance.
|
ESWC | 2016 | 1 |
| Detecting Change Processes in Dynamic Networks by Frequent Graph Evolution Rule Mining.
|
ICDM | 2016 | 12 |
| UrbanHubble: Location Prediction and Geo-Social Analytics in LBSN.
|
ECML/PKDD | 2015 | 1 |
| Gradient-based Signatures for Efficient Similarity Search in Large-scale Multimedia Databases.
|
CIKM | 2015 | 5 |
| MultiClust special issue on discovering, summarizing and using multiple clusterings.
|
MLJ | 2015 | 0 |
| Density-Based Subspace Clustering in Heterogeneous Networks.
|
ECML/PKDD | 2014 | 20 |
| Check-in Location Prediction Using Wavelets and Conditional Random Fields.
|
ICDM | 2014 | 15 |
| Efficient Filter Approximation Using the Earth Mover's Distance in Very Large Multimedia Databases with Feature Signatures.
|
CIKM | 2014 | 23 |
| SMVC: semi-supervised multi-view clustering in subspace projections.
|
KDD | 2014 | 21 |
| Detecting and exploring clusters in attributed graphs: a plugin for the gephi platform.
|
CIKM | 2013 | 13 |
| Spectral Subspace Clustering for Graphs with Feature Vectors.
|
ICDM | 2013 | 61 |
| Adaptive Model Tree for Streaming Data.
|
ICDM | 2013 | 3 |
| Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors.
|
PAKDD | 2013 | 44 |
| Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases.
|
PAKDD | 2012 | 7 |
| Multi-view clustering using mixture models in subspace projections.
|
KDD | 2012 | 35 |
| Effective and Robust Mining of Temporal Subspace Clusters.
|
ICDM | 2012 | 7 |
| Finding density-based subspace clusters in graphs with feature vectors.
|
DMKD | 2012 | 1 |
| Tracing clusters in evolving graphs with node attributes.
|
CIKM | 2012 | 10 |
| Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data.
|
KDD | 2012 | 17 |
| CC-MR - Finding Connected Components in Huge Graphs with MapReduce.
|
ECML/PKDD | 2012 | 29 |
| Tracing Evolving Subspace Clusters in Temporal Climate Data.
|
DMKD | 2012 | 24 |
| A tool for automated evaluation of algorithms.
|
CIKM | 2012 | 0 |
| Mining coherent subgraphs in multi-layer graphs with edge labels.
|
KDD | 2012 | 0 |
| Processing the signature quadratic form distance on many-core GPU architectures.
|
CIKM | 2011 | 12 |
| MOA: A Real-Time Analytics Open Source Framework.
|
ECML/PKDD | 2011 | 53 |
| Tracing Evolving Clusters by Subspace and Value Similarity.
|
PAKDD | 2011 | 16 |
| External evaluation measures for subspace clustering.
|
CIKM | 2011 | 56 |
| Scalable density-based subspace clustering.
|
CIKM | 2011 | 24 |
| DB-CSC: A Density-Based Approach for Subspace Clustering in Graphs with Feature Vectors.
|
ECML/PKDD | 2011 | 63 |
| An effective evaluation measure for clustering on evolving data streams.
|
KDD | 2011 | 93 |
| Modeling image similarity by Gaussian mixture models and the Signature Quadratic Form Distance.
|
ICCV | 2011 | 42 |
| Flexible Fault Tolerant Subspace Clustering for Data with Missing Values.
|
ICDM | 2011 | 19 |
| Subgraph Mining on Directed and Weighted Graphs.
|
PAKDD | 2010 | 16 |
| Adaptive outlierness for subspace outlier ranking.
|
CIKM | 2010 | 34 |
| Subspace Clustering Meets Dense Subgraph Mining: A Synthesis of Two Paradigms.
|
ICDM | 2010 | 125 |
| Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data.
|
ICDM | 2010 | 72 |
| Subspace Clustering for Uncertain Data.
|
SDM | 2010 | 34 |
| Bulk Loading Hierarchical Mixture Models for Efficient Stream Classification.
|
PAKDD | 2010 | 5 |
| SOREX: Subspace Outlier Ranking Exploration Toolkit.
|
ECML/PKDD | 2010 | 0 |
| DensEst: Density Estimation for Data Mining in High Dimensional Spaces.
|
SDM | 2009 | 46 |
| Exploring multimedia databases via optimization-based relevance feedback and the earth mover's distance.
|
CIKM | 2009 | 4 |
| Self-Adaptive Anytime Stream Clustering.
|
ICDM | 2009 | 73 |
| Detection of orthogonal concepts in subspaces of high dimensional data.
|
CIKM | 2009 | 47 |
| Harnessing the Strengths of Anytime Algorithms for Constant Data Streams.
|
ECML/PKDD | 2009 | 35 |
| Relevant Subspace Clustering: Mining the Most Interesting Non-redundant Concepts in High Dimensional Data.
|
ICDM | 2009 | 99 |
| Harnessing the strengths of anytime algorithms for constant data streams.
|
DMKD | 2009 | 0 |
| SubClass: Classification of Multidimensional Noisy Data Using Subspace Clusters.
|
PAKDD | 2008 | 6 |
| EDSC: efficient density-based subspace clustering.
|
CIKM | 2008 | 36 |
| INSCY: Indexing Subspace Clusters with In-Process-Removal of Redundancy.
|
ICDM | 2008 | 109 |
| Pleiades: Subspace Clustering and Evaluation.
|
ECML/PKDD | 2008 | 11 |
| Morpheus: interactive exploration of subspace clustering.
|
KDD | 2008 | 41 |
| DUSC: Dimensionality Unbiased Subspace Clustering.
|
ICDM | 2007 | 140 |
| CLICKS: an effective algorithm for mining subspace clusters in categorical datasets.
|
KDD | 2005 | 106 |