We formulate a simple approximate range query problem for time series data, and propose a method that aims to quickly access a small number of high quality ...

This thesis formulates a simple approximate range query problem for time series data, and proposes a method that aims to quickly access a small number of high- ...

Abstract—Efficient time series similarity search is a fundamental operation for data exploration and analysis. While previous work has focused on indexing ...

We formulate a simple approximate range query problem for time series data, and propose a method that aims to quickly access a small number of high quality ...

We formulate a simple approximate range query problem for time series data, and propose a method that aims to quickly access a small number of high quality ...

This work has been supervised by Professor Vipin Kumar, Karsten Steinhaeuser, and. Shyam Boriah, all of whom have been instrumental in guiding my academic ...

Efficient time series similarity search is a fundamental operation for data exploration and analysis. While previous work has focused on indexing ...

We propose a multi-resolution approximation (M-RA) of Gaussian processes observed at irregular locations in space. The M-RA process is specified as a linear ...

Jun 7, 2019 · Motivated by a large ground-level ozone dataset, we propose a new computationally effi- cient additive approximate Gaussian process. The ...

Spatiotemporal exploratory data analysis is a methodological approach to detect and describe patterns, trends, and relations in data in both space and time.