Papers One-Class Classification
“One-Class Classification” 태그가 달린 논문 227편 · 필터 해제
Robust Classification of High-Dimensional Spectroscopy Data Using Deep Learning and Data Synthesis
This paper presents a new approach to classification of high dimensional spectroscopy data and demonstrates that it outperforms other current state-of-the art approaches. The specific task we consider is identifying whet…
Binary ClassificationClassificationGeneral ClassificationOne-Class Classification+1Ellipsoidal Subspace Support Vector Data Description
In this paper, we propose a novel method for transforming data into a low-dimensional space optimized for one-class classification. The proposed method iteratively transforms data into a new subspace optimized for ellips…
General ClassificationOne-Class ClassificationMeta-SVDD: Probabilistic Meta-Learning for One-Class Classification in Cancer Histology Images
To train a robust deep learning model, one usually needs a balanced set of categories in the training data. The data acquired in a medical domain, however, frequently contains an abundance of healthy patients, versus a s…
General ClassificationMeta-LearningOne-Class ClassificationDROCC: Deep Robust One-Class Classification
Classical approaches for one-class problems such as one-class SVM and isolation forest require careful feature engineering when applied to structured domains like images. State-of-the-art methods aim to leverage deep lea…
Anomaly DetectionClassificationFeature EngineeringGeneral Classification+2One-Class Graph Neural Networks for Anomaly Detection in Attributed Networks
Nowadays, graph-structured data are increasingly used to model complex systems. Meanwhile, detecting anomalies from graph has become a vital research problem of pressing societal concerns. Anomaly detection is an unsuper…
Anomaly DetectionGeneral ClassificationGraph Anomaly DetectionGraph Neural Network+1Boosting rare benthic macroinvertebrates taxa identification with one-class classification
Insect monitoring is crucial for understanding the consequences of rapid ecological changes, but taxa identification currently requires tedious manual expert work and cannot be scaled-up efficiently. Deep convolutional n…
ClassificationGeneral ClassificationOne-Class ClassificationSimple and Effective Prevention of Mode Collapse in Deep One-Class Classification
Anomaly detection algorithms find extensive use in various fields. This area of research has recently made great advances thanks to deep learning. A recent method, the deep Support Vector Data Description (deep SVDD), wh…
Anomaly DetectionGeneral ClassificationOne-Class ClassificationComparison of Statistical and Machine Learning Techniques for Physical Layer Authentication
In this paper we consider authentication at the physical layer, in which the authenticator aims at distinguishing a legitimate supplicant from an attacker on the basis of the characteristics of a set of parallel wireless…
BIG-bench Machine LearningClusteringGeneral ClassificationOne-Class ClassificationUnsupervised Learning of the Set of Local Maxima
This paper describes a new form of unsupervised learning, whose input is a set of unlabeled points that are assumed to be local maxima of an unknown value function v in an unknown subset of the vector space. Two function…
Anomaly DetectionGeneral ClassificationOne-Class ClassificationUncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning
Robustness to out-of-distribution (OOD) data is an important goal in building reliable machine learning systems. Especially in autonomous systems, wrong predictions for OOD inputs can cause safety critical situations. As…
Bayesian InferenceClassificationDeep Reinforcement LearningGeneral Classification+4Implicit supervision for fault detection and segmentation of emerging fault types with Deep Variational Autoencoders
Data-driven fault diagnostics of safety-critical systems often faces the challenge of a complete lack of labeled data associated with faulty system conditions (i.e., fault types) at training time. Since an unknown number…
ClusteringFault DetectionOne-Class ClassificationOne-class classifier+2One-Class Classification by Ensembles of Regression models -- a detailed study
One-class classification (OCC) deals with the classification problem in which the training data has data points belonging only to target class. In this paper, we study a one-class classification algorithm, One-Class Clas…
ClassificationGeneral ClassificationOne-Class ClassificationregressionNFAD: Fixing anomaly detection using normalizing flows
Anomaly detection is a challenging task that frequently arises in practically all areas of industry and science, from fraud detection and data quality monitoring to finding rare cases of diseases and searching for new ph…
Anomaly DetectionBayesian InferenceBIG-bench Machine LearningBinary Classification+3Metre as a stylometric feature in Latin hexameter poetry
This paper demonstrates that metre is a privileged indicator of authorial style in classical Latin hexameter poetry. Using only metrical features, pairwise classification experiments are performed between 5 first-century…
ClassificationGeneral ClassificationOne-Class ClassificationHost-based anomaly detection using Eigentraces feature extraction and one-class classification on system call trace data
This paper proposes a methodology for host-based anomaly detection using a semi-supervised algorithm namely one-class classifier combined with a PCA-based feature extraction technique called Eigentraces on system call tr…
Anomaly DetectionIntrusion DetectionOne-Class ClassificationOne-class classifierStatistical and Machine Learning-based Decision Techniques for Physical Layer Authentication
In this paper we assess the security performance of key-less physical layer authentication schemes in the case of time-varying fading channels, considering both partial and no channel state information (CSI) on the recei…
BIG-bench Machine LearningGeneral ClassificationOne-Class ClassificationDomain Adaptation for One-Class Classification: Monitoring the Health of Critical Systems Under Limited Information
The failure of a complex and safety critical industrial asset can have extremely high consequences. Close monitoring for early detection of abnormal system conditions is therefore required. Data-driven solutions to this …
Domain AdaptationFault DetectionGeneral ClassificationOne-Class Classification+2Contextual One-Class Classification in Data Streams
In machine learning, the one-class classification problem occurs when training instances are only available from one class. It has been observed that making use of this class's structure, or its different contexts, may i…
ClassificationGeneral ClassificationOne-Class ClassificationOne-class classifierSelf-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text
There exist few text-specific methods for unsupervised anomaly detection, and for those that do exist, none utilize pre-trained models for distributed vector representations of words. In this paper we introduce a new ano…
Anomaly DetectionContextual Anomaly DetectionGeneral ClassificationOne-Class Classification+2Domain Adaptive Attention Learning for Unsupervised Person Re-Identification
Person re-identification (Re-ID) across multiple datasets is a challenging task due to two main reasons: the presence of large cross-dataset distinctions and the absence of annotated target instances. To address these tw…
DiversityDomain AdaptationGeneral ClassificationOne-Class Classification+2