The following papers have been accepted for presentation at AALTD’16 :
- Stephan Spiegel. Transfer Learning for Time Series Classification in Dissimilarity Spaces [pdf]
- Weiwei Shi, Yongxin Zhu, Xiao Pan, Philip Yu and Yufeng Chen. Missing Data Prediction in Multi-source Time Series with Sensor Network Regularization [pdf]
- Pierre-François Marteau. Assessing pattern recognition or labeling in streams of temporal data [pdf]
- David Tolpin. Progressive Temporal Window Widening [pdf]
- Katsiaryna Mirylenka, Christoph Miksovic and Paolo Scotton. Recurrent Neural Networks for Modeling Company-Product Time Series [pdf]
- Christina Papagiannopoulou, Diego Miralles, Mathieu Depoorter, Niko Verhoest, Wouter Dorigo and Willem Waegeman. Discovering relationships in climate-vegetation dynamics using satellite data [pdf]
- Yulong Pei, Jianpeng Zhang, George H. L. Fletcher and Mykola Pechenizkiy. Node Classification in Dynamic Social Networks [pdf]
- Arthur Le Guennec, Simon Malinowski and Romain Tavenard. Data Augmentation for Time Series Classification using Convolutional Neural Networks [pdf]
- Xavier Renard, Maria Rifqi, Gabriel Fricout and Marcin Detyniecki. EAST representation: fast discovery of discriminant temporal patterns from time series [pdf]
- Romain Brault, Néhémy Lim and Florence d’Alché-buc. Scaling up Vector Autoregressive Models With Operator-Valued Random Fourier Features [pdf]
- Pablo Montero-Manso and Jose A. Vilar. A time series two-sample test based on comparing distributions of pairwise distances [pdf]
