Temporal Machine Learning

Introduction

This page lists the researchers that I know about that work in the area. If you have any suggestions, people I've missed, etc., I would really appreciate it if you would contact me.

Dimensions of research

• Supervised vs Unsupervised: The temporal data can be labelled, telling us what type of pattern is, or alternatively the goal can be more difficult, along the lines of finding interesting and recurring patterns.
• Univariate vs Multivariate: Is a single "channel" of data being analysed, or is it a domain where there is more than one source of data that is simultaneously being analysed?

Reinventing the wheel?

• Hidden Markov Models
• Recurrent Neural Networks
• Allen's Interval Logic
• Knowledge-based signal processing

Researchers

• Gautam Das is doing work in finding similar time series.

• Doug Fisher is looking at techniques for clustering time series. In addition, two of his students have worked or are working on the problem:
  • Stefanos Manganaris has built a system for classifying univariate data streams for his PhD. His PhD also has a good literature survey for getting into the area.
  • Doug Talbert is looking at clustering temporal structures.

• Giorgios Paliouras did a PhD thesis on refining temporal recognition expert systems. He applied his techniques to whale songs. Also has a good literature survey, especially on knowledge-based signal processing.

• Eamonn Keogh is looking at ways of picking up patterns from temporal data.

• Heikki Mannila is interested in sequence data (like network logs) as well as time series (ECGs and the like). He has a wide range of papers available in the area.

• Padhraic Smyth also does some work in the area, as well a great deal of work on a lot of other topics related to time series analysis.

• Mohammed Waleed Kadous is developing a multivariate classification algorithm.

• Jeffrey D. Scargle is working on techniques for analysing time series from astronomical sources.

• Frank Hoeppner on the qualitative aspects of time series used by humans in analysing time series.

Data sets

• Heart Data: As used by Keogh, one of the datasets from the Nonlinear Techniques in Physiological Time Series Analysis datasets.

• Waleed Kadous's Sign Language Data collected by the author.
• The UCI KDD Archive now has several temporal datasets available.

Related Conferences & Workshops

• Predicting the future: AI Approaches to Time-series Analysis was held as a workshop to AAAI'98. It covered some of the most recent and interesting work in the area. The chair was Andrea Danyluk.

• Machine Learning for Spatial and Temporal Data is being held as a workshop as part of ICML 2001. It is being held in Williamstown, Massachusetts.

Related Journals

• Data Mining and Knowledge Discovery.

• Machine Learning Journal.

Reminder