Accepted Papers

    • Efficient spatio-temporal sampling via low-rank tensor sketching,
    • Rose Yu, Yan Liu, Sanjay Purushotham
    • [pdf]
    • Collaborative Multi-Output Gaussian Processes for Collections of Sparse Multivariate Time Series,
    • Steve Cheng-Xian Li, Benjamin Marlin
    • [pdf]
    • Stochastic Collapsed Variational Inference for Hidden Markov Models,
    • Pengyu Wang, Phil Blunsom
    • [pdf]
    • Minimax Time Series Prediction,
    • Wouter Koolen, Alan Malek, Peter Bartlett, Yasin Abbasi-Yadkori
    • [pdf]
    • Isotonic Hawkess Processes,
    • Yichen Wang, Nan Du, Le Song
    • [pdf]
    • Feature Extraction for Option Price Forecasting,
    • Dmitry Storcheus, Sergey Gelman
    • [pdf]
    • Multi-step predictive state representations,
    • Lucas Langer, Borja Balle, Doina Precup
    • [pdf]
    • Multivariate Time Series Classification Using Inter-Leaved Shapelets,
    • Om Prasad Patri, Rajgopal Kannan, Anand V. Panangadan, Viktor K. Prasanna
    • [pdf]
    • Functional Learning of Time Series Models Preserving Granger Causality Structures,
    • Magda Gregorova, Francesco Dinuzzo, Alexandros Kalousis
    • [pdf]
    • Early Classification of Time Series by Hidden Markov Models with Set-valued Parameters,
    • Alessandro Antonucci, Mauro Scanagatta, Denis D. Maua and Cassio P. de Campos
    • [pdf]
    • Design of Covariance Functions using Inter-Domain Inducing Variables,
    • Felipe Tobar, Thang Bui and Richard Turner
    • [pdf] (Best Paper Award)
    • Sparse Adaptive Prior for Time Dependent Model Parameters,
    • Dani Yogotama, Bryan R. Routledge, Noah A. Smith
    • [pdf]
    • Time Series Forecasting with Shared Seasonality Patterns using Non-Negative Matrix Factorization,
    • Wei Sun, Dmitry Malioutov
    • [pdf]
    • Multi-Instance Learning for Activity Recognition from Time Series Data Using A Mixture of Auto-Regressive Processes,
    • Xinze Guan, Raviv Raich, Weng-Keen Wong
    • [pdf] [supp]
    • ODE-augmented Training Improves Anomaly Detection in Sensor Data from Machines,
    • Mohit Yadav, Pankaj Malhotra, Lovekesh Vig, K Sriram, Gautam Shroff
    • [pdf]
    • Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path,
    • Daniel Hsu, Aryeh Kontorovich, Csaba Szepesvari
    • [pdf]
    • p-Markov GP for Scalable Expressive Online Bayessian Nonparametric Time Series Forecasting,
    • Yves-Laurent Kom Samo, Stephen J. Roberts
    • [pdf]
    • Temporal Regularized Matrix Factorization,
    • Hsiang-Fu Yu, Nikhil Rao, Inderjit S. Dhillon
    • [pdf]
    • Action Recognition using Visual Attention,
    • Shikhar Sharma, Ryan Kiros, Ruslan Salakhutdinov
    • [pdf]
    • Early Classification of Time Series from a Cost Minimization Point of View,
    • Usue Mori, Alexander Mendiburu, Sanjoy Dasgupta, Jose A. Lozano
    • [pdf]