Search Results for author:
Found 4 papers, 1 papers with code
Beyond Labels: Leveraging Deep Learning and LLMs for Content Metadata
We present some of the challenges associated with using genre label information and propose a new way of examining the genre information that we call as the \textit{Genre Spectrum}.
A Fast-Optimal Guaranteed Algorithm For Learning Sub-Interval Relationships in Time Series
Traditional approaches focus on finding relationships between two entire time series, however, many interesting relationships exist in small sub-intervals of time and remain feeble during other sub-intervals.
Mining Novel Multivariate Relationships in Time Series Data Using Correlation Networks
In many domains, there is significant interest in capturing novel relationships between time series that represent activities recorded at different nodes of a highly complex system.
Mining Sub-Interval Relationships In Time Series Data
In this paper, we define the notion of a sub-interval relationship (SIR) to capture inter- actions between two time series that are prominent only in certain sub-intervals of time.
