Accepted papers

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]

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