Multivariate time series classification is an important computational ta...
The state-of-the-art in time series classification has come a long way, ...
Wearable sensors such as Inertial Measurement Units (IMUs) are often use...
This paper aims to provide a framework to quantitatively evaluate and ra...
Goal: The countermovement jump (CMJ) is commonly used to measure the
exp...
In April 2022, the Vistamilk SFI Research Centre organized the second ed...
Technological advancements have spurred the usage of machine learning ba...
Accuracy is a key focus of current work in time series classification.
H...
Sentence compression reduces the length of text by removing non-essentia...
Remote monitoring of motor functions is a powerful approach for health
a...
Symbolic representations of time series have proven to be effective for ...
A chemometric data analysis challenge has been arranged during the first...
Cardiac Magnetic Resonance (CMR) is the most effective tool for the
asse...
Sequence classification is the supervised learning task of building mode...
The time series classification literature has expanded rapidly over the ...
Previous work on automatic news timeline summarization (TLS) leaves an
u...
Multi-document summarization (MDS) aims to compress the content in large...
Following a particular news story online is an important but difficult t...
The time series classification literature has expanded rapidly over the ...
Since 2013 researchers at University College Dublin in the Insight Centr...
Smoothed analysis is a framework for analyzing the complexity of an
algo...