Most time series data mining algorithms use similarity search as a core subroutine, and thus
the time taken for similarity search is the bottleneck for virtually all time series data mining …

The previous decade has brought a remarkable increase of the interest in applications that
deal with querying and mining of time series data. Many of the research efforts in this context …

The ubiquity of time series data across almost all human endeavors has produced a great
interest in time series data mining in the last decade. While dozens of classification …

Most time series data mining algorithms use similarity search as a core subroutine, and thus
the time taken for similarity search is the bottleneck for virtually all time series data mining …

Time series are ubiquitous, and a measure to assess their similarity is a core part of many
computational systems. In particular, the similarity measure is the most essential ingredient …

The ubiquity of time series data across almost all human endeavors has produced a great
interest in time series data mining in the last decade. While there is a plethora of …

In instruction conditioned navigation, agents interpret natural language and their
surroundings to navigate through an environment. Datasets for studying this task typically …

Similarity search is the core procedure for several time series mining tasks. While different
distance measures can be used for this purpose, there is clear evidence that the Dynamic …

Since time series are characterized by a substantial volume of data, high levels of noise and
the correlation between data in the time series attributes, it becomes challenging to mine …

For many years, neural networks have gained gigantic interest and their popularity is likely
to continue because of the success stories of deep learning. Nonetheless, their applications …