Time-dependent sequential data emerge in many key real-world problems, including areas such as climate, robotics, biology, economics, entertainment, healthcare and transportation. The increasing volume and complexity of time series data in modern applications highlight the importance of scalable and flexible time series learning techniques. Predominant methods in machine learning often assume i.i.d. observations, which is generally not appropriate for time series data. Therefore, there is both a great need and an exciting opportunity for the machine learning community to develop theory, models, and algorithms for processing and analyzing large-scale complex time series data.
The Time Series Workshop at ICML 2019 brings together theoretical and applied researchers at the forefront of time series analysis and algorithms to discuss existing key progress and promising new directions. Topics include methods for time series prediction, classification, clustering, anomaly and change point detection, causal discovery, and dimensionality reduction as well as a general theory for learning and analyzing stochastic processes. Our workshop will host leading researchers from academia and industry with a range of perspectives and interests. We also invite researchers from the related areas of batch and online learning, deep learning, reinforcement learning, data analysis and statistics, and many others to both contribute and participate in this workshop.
Due to our generous sponsors, we have a limited amount of funding to support the travel of graduate students and postdoctoral fellows (up to two years) to attend our workshop. These awards will be assigned primarily based on need and travel distance, and they will be limited to one individual per paper. If you or one of your authors would like to be considered for a travel award, please submit the following information to email@example.com no later than May 28th, 2019 11:59PM Pacific Time. 1) Workshop paper title; 2) Student / postdoctoral fellow name; 3) Student / postdoctoral fellow level; 4) Traveling from; 5) Reasons for needing support. The recipients of these travel awards will be notified by June 6th (updated from June 4th), 2019 11:59 PM Pacific Time.
|8:45 - 9:00||Opening Remarks|
|9:00 - 9:45||Invited Talk: Yulia Gel, Change Point Detection in Time Series through the Lens of Topological Data Analysis|
|9:45 - 10:00||Contributed Talk: Online Forecasting of Total-Variation-bounded Sequences (Dheeraj Baby and Yu-Xiang Wang)|
|10:00 - 10:15||Contributed Talk: Latent Ordinary Differential Equations for Irregularly-Sampled Time Series (Yulia Rubanova, Ricky T. Q. Chen and David Duvenaud)|
|10:15 - 10:30||Contributed Talk: BreizhCrops: A Satellite Time Series Dataset for Crop Type Identification (Marc Rußwurm, Sébastien Lefèvre and Marco Körner)|
|10:30 - 11:00||Morning Coffee Break|
|11:00 - 11:45||Invited Talk: Suchi Saria, Addressing Failures from Feedback Loops in Designing Decision Aids|
|11:45 - 12:30||Poster Session|
|12:30 - 14:30||Lunch|
|14:30 - 14:45||Contributed Talk: Neural time series models with GluonTS (Alexander Alexandrov et. al.)|
|14:45 - 15:00||Contributed Talk: Latent Spectrum Gaussian Processes (Jayson Salkey, Greg Benton, Wesley Maddox, Julio Albinati and Andrew Wilson)|
|15:00 - 15:30||Panel Discussion|
|15:30 - 16:00||Afternoon Coffee Break|
|16:00 - 16:30||Poster Session|
|16:30 - 17:15||Invited Talk: Yan Liu, Artificial Intelligence for Smart Transportation|
|17:15 - 18:00||Invited Talk: Edo Liberty, Streaming algorithms, Apache DataScketches, and new results on corsets|
|18:00 - 18:05||Awards and Closing Remarks|
University of Texas at Dallas
Johns Hopkins University
University of Southern California
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. Supplementary material is permitted, although there is no guarantee that it will be reviewed. As the review process is not blind, authors can reveal their identity in their submissions. All inquiries may be sent to firstname.lastname@example.org.
Submissions page: Times Series Workshop 2019.
Note on open dataset submissions: In order to promote new and innovative research in time series research, we plan to accept a small number of 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.
Note on dual submission and publication policy: We accept dual submissions with other conferences, workshops, and/or journals. Accepted papers will be posted on the workshop website. However, there will not be any formal proceedings, so authors should feel free to submit their accepted work to other venues in the future (subject to the submission policy of those venues).
Paper Submission Deadline: May 3, 2019, 11:59 PM PST
Author Notification: May 20, 2019, 11:59 PM PST (changed from May 17, 2019, 11:59PM PST)
Travel Award Application Due: May 28, 2019, 11:59 PM PST
Travel Award Notification: June 6 (changed from June 4th), 2019, 11:59 PM PST
Final Version: June 13, 2019, 11:59 PM PST
Workshop: June 14, 2019