TimeSeriesWorkshop@ICML19: Time Series Workshop @ ICML 2019 |
Website | http://roseyu.com/time-series-workshop/ |
Submission link | https://easychair.org/conferences/?conf=timeseriesicml19 |
Submission deadline | May 3, 2019 |
Call for papers and open datasets
June 14th or 15th, 2019
Long Beach, CA, USA
http://roseyu.com/time-series-workshop/
Important dates:
Submission deadline: May 3rd, 2019
Decision notification: May 17th, 2019
Overview
Time series data is ubiquitous. In domains as diverse as finance, entertainment, transportation, climate science, and health-care, there has been a fundamental shift away from parsimonious, infrequent measurement to nearly continuous monitoring and recording. Rapid advances in many sensing technologies, ranging from remote sensors to wearables and social sensing, are have generated a rapid growth in the size and complexity of time series archives. Thus, while time series analysis has been studied extensively in the past, its importance only continues to grow. Furthermore, modern time series data pose significant new challenges in terms of structure (e.g., irregular sampling in hospital records and spatiotemporal structure in climate data) and size (e.g. computation and storage). These challenges are compounded by the fact that the standard i.i.d. assumptions used in other areas of machine learning are often not appropriate for time series. Instead, new theory, models and algorithms are needed to process and analyze this data.
The goal of this workshop is to bring together both theoretical and applied researchers interested in the analysis of time series and the development of new algorithms to process sequential data. This includes researchers working on specific tasks such as time series prediction, classification, clustering, anomaly and change point detection, correlation discovery, dimensionality reduction as well as researchers working on developing a general theory for learning and understanding stochastic processes. We also invite researchers from related areas, including but not limited to batch and online learning, reinforcement learning, data analysis and statistics, and econometrics, to contribute to this workshop.
Submission Guidelines
We invite researchers to submit both theoretical and applied work on time series analysis, modeling, and algorithms, along with their applications. Papers submitted to the workshop should be up to four pages long excluding references and in ICML 2019 format. The review process is not blind, so authors should feel free to reveal their identity in their submissions.
Note on open dataset submissions: in order to promote new and innovative research in time series research, we plan to accept high-quality time series dataset contributions. These submissions should be accompanied by a clear and detailed description of the dataset, some potential questions and applications that arise from it, as well as discussion on why the data cannot be sufficiently modeled using traditional batch learning techniques. Preliminary empirical investigations conveying any insight about the data will increase the quality of the submission.
Submissions page: https://easychair.org/conferences/?conf=timeseriesicml19.
Organizers & Contact
- Vitaly Kuznetsov, Google Research
- Cheng Tang, Amazon AI
- Yuyang Wang, Amazon AI
- Scott Yang, D.E. Shaw & Co.
- Rose Yu, Northeastern University
Any inquiries about the workshop or submission process may be sent to: tswicml2019@gmail.com.