MSDMA Reading Group

• 29/11/18: "Asynchronous Methods for Deep Reinforcement Learning", V. Mnih, A.P. Badia, M. Mirza, A. Graves, T. Harley, T. P. Lillicrap, D. Silver, K. Kavukcuoglu. ICML'16.
  Presented by Laura Calem. [slides]
• 19/10/18: "Graph Convolutional Neural Networks for Web-Scale Recommender Systems", R. Ying, R. He, K. Chen, P. Eksombatchai, W. L. Hamilton, J. Leskovec. KDD'18.
  Presented by Raphael Fournier-S'niehotta. [slides]
• 08/06/18: "Zero-Shot Learning: the Good, the Bad and the Ugly", Yongqin Xian, Bernt Schiele, Zeynep Akata. CVPR'17.
  Presented by Yannick Le Cacheux [slides]
• 04/05/18: "Decoys selection in benchmarking datasets".
  Presented by Matthieu Montes.
• 02/03/18: "Attention is all you need", Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser. NIPS'17.
  Presented by Serge Rosmorduc. [slides]
• 12/01/18: "Invariance and Stability of Deep Convolutional Representations", Alberto Bietti, Julien Mairal, NIPS'17.
  Presented by Nicolas Thome [slides]
• 10/11/17: "Missing Modalities Imputation via Cascaded Residual Autoencoder", Luan Tran, Xiaoming Liu, Jiayu Zhou, Rong Jin. CVPR'17.
  Presented by Vincent Audigier. [slides]
• 06/10/17: "Planning and Analyzing Experiments with Models that Distinguish Between Replicates and Repeats", Michael S. Hamada, Stefan H. Steiner, R. Jock MacKay, C. Shane Reese.
  Presented by Luan Jaupi
• 23/06/17: "Partial Least Squares Path Modeling: matching Models and Modes".
  Presented by Giorgio Russolillo. [slides]
• 24/05/17: "Prediction for clusterwise multiblock regression".
  Presented by Ndeye Niang.
• 28/04/17: "Dropout as Bayesian Appoximation: Representing Model Uncertainty in Deep Learning", Yarin Gal, Zoubin Ghahramani. ICML'16.
  Presented by Nicolas Thome [slides]