A signal processing approach to fair surface design
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
The complexity of the matrix eigenproblem
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Implicit fairing of irregular meshes using diffusion and curvature flow
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
LOF: identifying density-based local outliers
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Semi-supervised outlier detection
Proceedings of the 2006 ACM symposium on Applied computing
Data Fusion and Multicue Data Matching by Diffusion Maps
IEEE Transactions on Pattern Analysis and Machine Intelligence
Clustering and Embedding Using Commute Times
IEEE Transactions on Pattern Analysis and Machine Intelligence
One-Class Classification by Combining Density and Class Probability Estimation
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on 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
ACM Computing Surveys (CSUR)
A Small Sphere and Large Margin Approach for Novelty Detection Using Training Data with Outliers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vague One-Class Learning for Data Streams
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
A hierarchical segmentation of articulated bodies
SGP '08 Proceedings of the Symposium on Geometry Processing
A concise and provably informative multi-scale signature based on heat diffusion
SGP '09 Proceedings of the Symposium on Geometry Processing
ACM Transactions on Graphics (TOG)
Mass estimation and its applications
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Discovery of Gait Anomalies from Motion Sensor Data
ICTAI '10 Proceedings of the 2010 22nd IEEE International Conference on Tools with Artificial Intelligence - Volume 02
Finding Local Anomalies in Very High Dimensional Space
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Anomaly Detection Using an Ensemble of Feature Models
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Semi-Supervised Novelty Detection
The Journal of Machine Learning Research
A Robust Clustering Algorithm Based on Aggregated Heat Kernel Mapping
ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
Isolation-Based Anomaly Detection
ACM Transactions on Knowledge Discovery from Data (TKDD)
Fast approximated power iteration subspace tracking
IEEE Transactions on Signal Processing - Part I
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Current popular anomaly detection algorithms are capable of detecting global anomalies but oftentimes fail to distinguish local anomalies from normal instances. This paper aims to improve unsupervised anomaly detection via the exploration of physics-based diffusion space. Building upon the embedding manifold derived from diffusion maps, we devise Local Anomaly Descriptor (LAD) whose originality results from faithfully preserving intrinsic and informative density-relevant neighborhood information. This robust and effective algorithm is designed with a weighted umbrella Laplacian operator to bridge global and local properties. To further enhance the efficacy of our proposed algorithm, we explore the utility of anisotropic Gaussian kernel (AGK) which can offer better manifold-aware affinity information. Comprehensive experiments on both synthetic and UCI real datasets verify that our LAD outperforms existing anomaly detection algorithms.