Call for papers

We solicit the submission of research papers in the following areas:

• time series prediction
• spatio-temporal forecasting
• time series classification
• clustering
• anomaly and change point detection
• correlation discovery
• dimensionality reduction
• model selection and ensemble learning for time series
• online learning and time series analysis
• general theory for learning with stochastic processes

We invite researchers from the related areas of batch and online learning, reinforcement learning, data analysis and statistics, econometrics, and others to join and contribute to this workshop.

Submissions must adhere to the NIPS 2017 style format available here. Papers may be a maximum of four pages long, including figures. An additional two pages containing cited references will be permitted. Supplementary material may also be provided, but may not be reviewed. The review process will be single-blind; the reviewers will know the identities of the authors.

Submissions page: NIPS 2017 Time Series Workshop.

All accepted papers will have a poster presentation, and a select few will also be chosen for oral presentations.

Please direct all inquiries about the submission process to: tsw.nips2017@gmail.com.

Important dates:

• Submission deadline: November 1st, 2017, 11:59 PM PST.
• Acceptance decisions: November 10th, 2017.
• Camera-ready version: November 30th, 2017, 11:59 PM PST.

NOTE: Early registration deadline for the conference is Oct. 26, but you can cancel your registration until Nov. 16. (see https://nips.cc/

for details). We highly recommend registering for the conference ahead of time to guarantee that you can participate in the workshop.