LOF: identifying density-based local outliers
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Efficient algorithms for mining outliers from large data sets
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Fast Outlier Detection in High Dimensional Spaces
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Ensembles of Learning Machines
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Cluster ensembles --- a knowledge reuse framework for combining multiple partitions
The Journal of Machine Learning Research
Analysis of Consensus Partition in Cluster Ensemble
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Combining Multiple Clusterings Using Evidence Accumulation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature bagging for outlier detection
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Clustering Ensembles: Models of Consensus and Weak Partitions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparing clusterings: an axiomatic view
ICML '05 Proceedings of the 22nd international conference on Machine learning
Outlier detection by active learning
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Converting Output Scores from Outlier Detection Algorithms into Probability Estimates
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
ACM Transactions on Knowledge Discovery from Data (TKDD)
Moderate diversity for better cluster ensembles
Information Fusion
Angle-based outlier detection in high-dimensional data
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Local peculiarity factor and its application in outlier detection
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Statistical Analysis and Data Mining
A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
ACM Computing Surveys (CSUR)
Characterization and evaluation of similarity measures for pairs of clusterings
Knowledge and Information Systems
A principled and flexible framework for finding alternative clusterings
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
LoOP: local outlier probabilities
Proceedings of the 18th ACM conference on Information and knowledge management
Adaptive cluster ensemble selection
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Artificial Intelligence Review
Selecting diversifying heuristics for cluster ensembles
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Finding natural clusters using multi-clusterer combiner based on shared nearest neighbors
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Unifying dependent clustering and disparate clustering for non-homogeneous data
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Relative clustering validity criteria: A comparative overview
Statistical Analysis and Data Mining
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Statistical selection of relevant subspace projections for outlier ranking
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Ranking outliers using symmetric neighborhood relationship
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Mining outliers with ensemble of heterogeneous detectors on random subspaces
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Isolation-Based Anomaly Detection
ACM Transactions on Knowledge Discovery from Data (TKDD)
Anomaly Detection for Discrete Sequences: A Survey
IEEE Transactions on Knowledge and Data Engineering
HiCS: High Contrast Subspaces for Density-Based Outlier Ranking
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
A survey on unsupervised outlier detection in high-dimensional numerical data
Statistical Analysis and Data Mining
A survey on enhanced subspace clustering
Data Mining and Knowledge Discovery
Outlier Analysis
Outlier Ranking via Subspace Analysis in Multiple Views of the Data
ICDM '12 Proceedings of the 2012 IEEE 12th International Conference on Data Mining
Outlier ensembles: position paper
ACM SIGKDD Explorations Newsletter
On the combination of relative clustering validity criteria
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
Subsampling for efficient and effective unsupervised outlier detection ensembles
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Systematic construction of anomaly detection benchmarks from real data
Proceedings of the ACM SIGKDD Workshop on Outlier Detection and Description
Cluster ensemble selection based on relative validity indexes
Data Mining and Knowledge Discovery
Data Mining and Knowledge Discovery
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Ensembles for unsupervised outlier detection is an emerging topic that has been neglected for a surprisingly long time (although there are reasons why this is more difficult than supervised ensembles or even clustering ensembles). Aggarwal recently discussed algorithmic patterns of outlier detection ensembles, identified traces of the idea in the literature, and remarked on potential as well as unlikely avenues for future transfer of concepts from supervised ensembles. Complementary to his points, here we focus on the core ingredients for building an outlier ensemble, discuss the first steps taken in the literature, and identify challenges for future research.