activity
20182023
most citedBenchmarking Multivariate Time Series Classification Algorithms

476 citations · 962 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2023

Composable Core-sets for Diversity Approximation on Multi-Dataset Streams

Stephanie Wang, Michael Flynn, Fangyu Luo

Core-sets refer to subsets of data that maximize some function that is commonly a diversity or group requirement. These subsets are used in place of the original data to accomplish…

cs.LG2021★ 320 cited

HIVE-COTE 2.0: a new meta ensemble for time series classification

Matthew Middlehurst, James Large, Michael Flynn +3

The Hierarchical Vote Collective of Transformation-based Ensembles (HIVE-COTE) is a heterogeneous meta ensemble for time series classification. HIVE-COTE forms its ensemble from cl…

cs.LG2020★ 476 cited

Benchmarking Multivariate Time Series Classification Algorithms

Alejandro Pasos Ruiz, Michael Flynn, Anthony Bagnall

Time Series Classification (TSC) involved building predictive models for a discrete target variable from ordered, real valued, attributes. Over recent years, a new set of TSC algor…

cs.LG2020★ 42 cited

A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1.0

Anthony Bagnall, Michael Flynn, James Large +2

The Hierarchical Vote Collective of Transformation-based Ensembles (HIVE-COTE) is a heterogeneous meta ensemble for time series classification. Since it was first proposed in 2016,…

cs.SD2019

WHAM!: Extending Speech Separation to Noisy Environments

Gordon Wichern, Joe Antognini, Michael Flynn +5

Recent progress in separating the speech signals from multiple overlapping speakers using a single audio channel has brought us closer to solving the cocktail party problem. Howeve…

cs.LG2018★ 95 cited

The UEA multivariate time series classification archive, 2018

Anthony Bagnall, Hoang Anh Dau, Jason Lines +5

In 2002, the UCR time series classification archive was first released with sixteen datasets. It gradually expanded, until 2015 when it increased in size from 45 datasets to 85 dat…

cs.LG2018★ 29 cited

Is rotation forest the best classifier for problems with continuous features?

A. Bagnall, M. Flynn, J. Large +3

In short, our experiments suggest that yes, on average, rotation forest is better than the most common alternatives when all the attributes are real-valued. Rotation forest is a tr…