Change-point detection in time-series data by relative density-ratio estimation
The objective of change-point detection is to discover abrupt property changes lying behind
time-series data. In this paper, we present a novel statistical change-point detection …
time-series data. In this paper, we present a novel statistical change-point detection …
Change point detection in time series data using autoencoders with a time-invariant representation
Change point detection (CPD) aims to locate abrupt property changes in time series data.
Recent CPD methods demonstrated the potential of using deep learning techniques, but …
Recent CPD methods demonstrated the potential of using deep learning techniques, but …
Predictive maintenance for residential air conditioning systems with smart thermostat data using modified Mann-Kendall tests
F Guo, B Rasmussen - Applied Thermal Engineering, 2023 - Elsevier
Predictive maintenance through fault detection and diagnosis (FDD) is an effective approach
to correct soft faults in residential air conditioners before complete failure. In particular …
to correct soft faults in residential air conditioners before complete failure. In particular …
Time series segmentation through automatic feature learning
Internet of things (IoT) applications have become increasingly popular in recent years, with
applications ranging from building energy monitoring to personal health tracking and activity …
applications ranging from building energy monitoring to personal health tracking and activity …
Rapid detection of maintenance induced changes in service performance
Service quality in operational IP networks can be impacted due to planned or unplanned
maintenance. During any maintenance activity, the responsibility of the operations team is to …
maintenance. During any maintenance activity, the responsibility of the operations team is to …
Penalized Partial Least Squares with applications to B-spline transformations and functional data
We propose a novel framework that combines penalization techniques with Partial Least
Squares (PLS). We focus on two important applications.(1) We combine PLS with a …
Squares (PLS). We focus on two important applications.(1) We combine PLS with a …
A review of changepoint detection models
Y Li, G Lin, T Lau, R Zeng - arXiv preprint arXiv:1908.07136, 2019 - arxiv.org
The objective of the change-point detection is to discover the abrupt property changes lying
behind the time-series data. In this paper, we firstly summarize the definition and in-depth …
behind the time-series data. In this paper, we firstly summarize the definition and in-depth …
Rapid and robust impact assessment of software changes in large internet-based services
The detection of performance changes in software change roll-outs in Internet-based
services is crucial for an operations team, because it allows timely roll-back of a software …
services is crucial for an operations team, because it allows timely roll-back of a software …
Funnel: Assessing software changes in web-based services
The detection of performance changes in software change roll-outs in Internet-based
services is crucial for an operations team, because it allows timely roll-back of a software …
services is crucial for an operations team, because it allows timely roll-back of a software …
Specview: malware spectrum visualization framework with singular spectrum transformation
With the rapid development of automation tools including polymorphic and metamorphic
engines, generic packers, and genetic programming, many variants of malware have …
engines, generic packers, and genetic programming, many variants of malware have …