NOVELTY DETECTION WITH MULTIVARIATE EXTREME VALUE THEORY, PART I: A NUMERICAL APPROACH TO MULTIMODAL ESTIMATION

NOVELTY DETECTION WITH MULTIVARIATE EXTREME VALUE THEORY, PART I: A NUMERICAL APPROACH TO MULTIMODAL ESTIMATION

Show other versions (1)

Extreme Value Theory (EVT) describes the distribution of data considered extreme with respect to some generative distribution, effectively modelling the tails of that distribution. In novelty detection, we wish to determine if data are "normal" with respect to some model of normality. If t...

Full description

Bibliographic Details
Main Authors:	Clifton, D, Hugueny, S, Tarassenko, L, IEEE
Format:	Conference item
Published:	2009

Similar Items

Novelty detection with multivariate extreme value theory, part I: A numerical approach to multimodal estimation
by: Clifton, D, et al.
Published: (2009)

NOVELTY DETECTION WITH MULTIVARIATE EXTREME VALUE THEORY, PART II: AN ANALYTICAL APPROACH TO UNIMODAL ESTIMATION
by: Hugueny, S, et al.
Published: (2009)

A COMPARISON OF APPROACHES TO MULTIVARIATE EXTREME VALUE THEORY FOR NOVELTY DETECTION
by: Clifton, D, et al.
Published: (2009)

Novelty detection with multivariate extreme value statistics
by: Clifton, D, et al.
Published: (2010)

Probabilistic Patient Monitoring with Multivariate, Multimodal Extreme Value Theory
by: Hugueny, S, et al.
Published: (2011)

An extreme function theory for novelty detection
by: Clifton, D, et al.
Published: (2012)

Probabilistic patient monitoring using extreme value theory: A multivariate, multimodal methodology for detecting patient deterioration
by: Hugueny, S, et al.
Published: (2010)

Novelty detection with extreme value theory in vital-sign monitoring
by: Hugueny, S, et al.
Published: (2013)

Extending the generalised Pareto distribution for novelty detection in high-dimensional spaces
by: Clifton, D, et al.
Published: (2013)

Bayesian extreme value statistics for novelty detection in gas-turbine engines
by: Clifton, D, et al.
Published: (2008)

PINNING THE TAIL ON THE DISTRIBUTION: A MULTIVARIATE EXTENSION TO THE GENERALISED PARETO DISTRIBUTION
by: Clifton, D, et al.
Published: (2011)

On-line Novelty Detection Using the Kalman Filter and Extreme Value Theory
by: Lee, H, et al.
Published: (2008)

A review of novelty detection
by: Pimentel, M, et al.
Published: (2014)

Automated novelty detection in industrial systems
by: Clifton, D, et al.
Published: (2008)

Novelty detection in large-vehicle turbocharger operation
by: Clifton, D, et al.
Published: (2007)

Learning shape for jet engine novelty detection
by: Clifton, D, et al.
Published: (2006)

Probabilistic novelty detection with support vector machines
by: Clifton, L, et al.
Published: (2014)

A framework for novelty detection in jet engine vibration data
by: Clifton, D, et al.
Published: (2007)

Extreme value statistics for novelty detection in biomedical data processing
by: Roberts, S
Published: (2000)

Extreme value statistics for novelty detection in biomedical signal processing
by: Roberts, S, et al.
Published: (2000)

Novelty Detection for Identifying Deterioration in Emergency Department Patients
by: Clifton, D, et al.
Published: (2011)

Point process models for novelty detection on spatial point patterns and their extremes
by: Luca, SE, et al.
Published: (2018)

Application of an intuitive novelty metric for jet engine condition monitoring
by: Clifton, D, et al.
Published: (2006)

Novelty detection for the identification of abnormalities
by: Tarassenko, L, et al.
Published: (2000)

A PROBABILISTIC RESOURCE ALLOCATING NETWORK FOR NOVELTY DETECTION
by: Roberts, S, et al.
Published: (1994)

Choosing an appropriate model for novelty detection
by: Nairac, A, et al.
Published: (1997)

Estimating strategies for multiparameter Multivariate Extreme Value copulas
by: G. Salvadori, et al.
Published: (2011-01-01)

Novelty effects in a multimodal warning signal.
by: Rowe, C, et al.
Published: (1999)

Combined support vector novelty detection for multi-channel combustion data
by: Clifton, L, et al.
Published: (2007)

Support vector novelty detection applied to Jet Engine vibration spectra
by: Hayton, P, et al.
Published: (2001)

Portfolio Tail Risk: A Multivariate Extreme Value Theory Approach
by: Miloš Božović
Published: (2020-12-01)

Probabilistic estimation of respiratory rate using gaussian processes
by: Pimentel, M, et al.
Published: (2013)

Static and dynamic novelty detection methods for jet engine health monitoring.
by: Hayton, P, et al.
Published: (2007)

Static and dynamic novelty detection methods for jet engine health monitoring
by: Hayton, P, et al.
Published: (2007)

How should novelty be valued in science?
by: Barak A Cohen
Published: (2017-07-01)

Database retrieval for novelty detection
by: Ong, Chun Lin.
Published: (2009)

Testing Conditions and Estimating Parameters in Extreme Value Theory
by: Helena Penalva, et al.
Published: (2019-04-01)

The Experience of Novelty and the Novelty of Experience
by: Liubov Skavronskaya, et al.
Published: (2020-02-01)

Estimation of the value-at-risk parameter: Econometric analysis and the extreme value theory approach
by: Mladenović Zorica, et al.
Published: (2006-01-01)

Complex Background Reconstruction for Novelty Detection
by: Kun Zhao, et al.
Published: (2023-09-01)