Accepted Papers

Papers marked with * will also appear as a part of JMLR Proceedings.

* Souhaib Ben Taieb. Sparse and Smooth Adjustments for Coherent Forecasts in Temporal Aggregation of Time Series
Shengdong Zhang, Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott and Mohak Shah. Event Prediction using Symbolization and Deep Learning
* Chen Luo and Anshumali Shrivastava. SSH (Sketch, Shingle, & Hash) for Indexing Massive-Scale Time Series
* Muhammad Amjad and Devavrat Shah. Trading Bitcoin and Online Time Series Prediction
* Gautier Marti, Sebastien Andler, Frank Nielsen and Philippe Donnat. Exploring and measuring non-linear correlations: Copulas, Lightspeed Transportation and Clustering
Mahdi Karami, Martha White and Dale Schuurmans. Optimal Linear Dynamical System Identification
Francois Belletti, Evan Sparks, Alexandre Bayen and Joseph Gonzalez. Scalable Linear Causal Inference for Irregularly Sampled Time Series with Long Range Dependencies
* Qunwei Li, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Zhenliang Zhang and Pramod Varshney. Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models
* Marina Riabiz, Tohid Ardeshiri and Simon Godsill. A central limit theorem with application to inference in $\alpha$-stable regression models
Michael Bertolacci, Edward Cripps, Sally Cripps and John Lau. Bayesian mixture models for multivariate time series with an application to Australian rainfall data
Luca Ambrogioni and Eric Maris. Analysis of Nonstationary Time Series Using Locally Coupled Gaussian Processes
Michael Rabadi. Co-adaptive learning over a countable space.
Simone Carlo Surace and Jean-Pascal Pfister. Online Maximum Likelihood Estimation of the Parameters of Partially Observed Diffusion Processes
Jingkang Yang, Haohan Wang, Jun Zhu and Eric Xing. SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data
Samaneh Khoshrou and Jaime S. Cardoso. Towards Never-Ending Learning From Parallel Time-Series
Nico S. Gorbach, Stefan Bauer and Joachim M. Buhmann. Inferring Non-linear State Dynamics using Gaussian Processes
Christopher Xie, Alex Tank and Emily Fox. A Unified Framework for Missing Data and Cold Start Prediction for Time Series Data
Pavel Filonov, Andrey Lavrentyev and Artem Vorontsov. Multivariate Industrial Time Series with Cyber-Attack Simulation: Fault Detection Using an LSTM-based Predictive Data Model
Ludovic Dos Santos, Ali Ziat, Ludovic Denoyer, Benjamin Piwowarski and Patrick Gallinari. Modeling Relational Time Series using Gaussian Embeddings
Kira Kempinska and John Shawe-Taylor. Improved Particle Filters for Vehicle Localisation
Igor Kulev, Pearl Pu and Boi Faltings. Discovering Persuasion Profiles Using Time Series Data
Daiki Suehiro, Kengo Kuwahara, Kohei Hatano and Eiji Takimoto. Time Series Classification Based on Random Shapelets
Subhro Das, Prasanth Lade and Srinivasan Soundar. Model adaptation and unsupervised learning with non-stationary batch data under smooth concept drift