970 citations · 2k across the 18 of their papers we have counts for
20 papers
Computing Divergences between Discrete Decomposable Models
Loong Kuan Lee, Nico Piatkowski, François Petitjean +1
There are many applications that benefit from computing the exact divergence between 2 discrete probability measures, including machine learning. Unfortunately, in the absence of a…
Tight lower bounds for Dynamic Time Warping
Geoffrey I. Webb, Francois Petitjean
Dynamic Time Warping (DTW) is a popular similarity measure for aligning and comparing time series. Due to DTW's high computation time, lower bounds are often employed to screen poo…
Elastic Similarity and Distance Measures for Multivariate Time Series
Ahmed Shifaz, Charlotte Pelletier, Francois Petitjean +1
This paper contributes multivariate versions of seven commonly used elastic similarity and distance measures for time series data analytics. Elastic similarity and distance measure…
Discriminative, Generative and Self-Supervised Approaches for Target-Agnostic Learning
Yuan Jin, Wray Buntine, Francois Petitjean +1
Supervised learning, characterized by both discriminative and generative learning, seeks to predict the values of single (or sometimes multiple) predefined target attributes based…
Seasonal Averaged One-Dependence Estimators: A Novel Algorithm to Address Seasonal Concept Drift in High-Dimensional Stream Classification
Rakshitha Godahewa, Trevor Yann, Christoph Bergmeir +1
Stream classification methods classify a continuous stream of data as new labelled samples arrive. They often also have to deal with concept drift. This paper focuses on seasonal d…
Time Series Extrinsic Regression
Chang Wei Tan, Christoph Bergmeir, Francois Petitjean +1
This paper studies Time Series Extrinsic Regression (TSER): a regression task of which the aim is to learn the relationship between a time series and a continuous scalar variable;…
Monash University, UEA, UCR Time Series Extrinsic Regression Archive
Chang Wei Tan, Christoph Bergmeir, Francois Petitjean +1
Time series research has gathered lots of interests in the last decade, especially for Time Series Classification (TSC) and Time Series Forecasting (TSF). Research in TSC has great…
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
Angus Dempster, François Petitjean, Geoffrey I. Webb
Most methods for time series classification that attain state-of-the-art accuracy have high computational complexity, requiring significant training time even for smaller datasets,…
Time series classification for varying length series
Chang Wei Tan, Francois Petitjean, Eamonn Keogh +1
Research into time series classification has tended to focus on the case of series of uniform length. However, it is common for real-world time series data to have unequal lengths.…
TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification
Ahmed Shifaz, Charlotte Pelletier, Francois Petitjean +1
Time Series Classification (TSC) has seen enormous progress over the last two decades. HIVE-COTE (Hierarchical Vote Collective of Transformation-based Ensembles) is the current sta…
Automatic alignment of surgical videos using kinematic data
Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber +3
Over the past one hundred years, the classic teaching methodology of "see one, do one, teach one" has governed the surgical education systems worldwide. With the advent of Operatio…
Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series
Charlotte Pelletier, Geoffrey I. Webb, Francois Petitjean
New remote sensing sensors now acquire high spatial and spectral Satellite Image Time Series (SITS) of the world. These series of images are a key component of classification syste…
Proximity Forest: An effective and scalable distance-based classifier for time series
Benjamin Lucas, Ahmed Shifaz, Charlotte Pelletier +5
Research into the classification of time series has made enormous progress in the last decade. The UCR time series archive has played a significant role in challenging and guiding…
Elastic bands across the path: A new framework and methods to lower bound DTW
Chang Wei Tan, Francois Petitjean, Geoffrey I. Webb
There has been renewed recent interest in developing effective lower bounds for Dynamic Time Warping (DTW) distance between time series. These have many applications in time series…
On the Inter-relationships among Drift rate, Forgetting rate, Bias/variance profile and Error
Nayyar A. Zaidi, Geoffrey I. Webb, Francois Petitjean +1
We propose two general and falsifiable hypotheses about expectations on generalization error when learning in the context of concept drift. One posits that as drift rate increases,…
Accurate parameter estimation for Bayesian Network Classifiers using Hierarchical Dirichlet Processes
Francois Petitjean, Wray Buntine, Geoffrey I. Webb +1
This paper introduces a novel parameter estimation method for the probability tables of Bayesian network classifiers (BNCs), using hierarchical Dirichlet processes (HDPs). The main…
Understanding Concept Drift
Geoffrey I. Webb, Loong Kuan Lee, François Petitjean +1
Concept drift is a major issue that greatly affects the accuracy and reliability of many real-world applications of machine learning. We argue that to tackle concept drift it is im…
Characterizing Concept Drift
Geoffrey I. Webb, Roy Hyde, Hong Cao +2
Most machine learning models are static, but the world is dynamic, and increasing online deployment of learned models gives increasing urgency to the development of efficient and e…
Deep Broad Learning - Big Models for Big Data
Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman +1
Deep learning has demonstrated the power of detailed modeling of complex high-order (multivariate) interactions in data. For some learning tasks there is power in learning models t…
Skopus: Mining top-k sequential patterns under leverage
Francois Petitjean, Tao Li, Nikolaj Tatti +1
This paper presents a framework for exact discovery of the top-k sequential patterns under Leverage. It combines (1) a novel definition of the expected support for a sequential pat…