Europe
Discriminative Topic Modeling with Logistic LDA
Iryna Korshunova, Hanchen Xiong, Mateusz Fedoryszak, Lucas Theis
Neural Information Processing Systems http://nips.cc/
d81ecfc8fb18e833a3fa0a35d92532b8-Paper-Conference.pdf
French, and Mandarin individuals recorded with functional Magnetic Resonance Imaging (fMRI), while they listened to approximately one hour of audio books. First, we show that this algorithm learns brain-like representations with as little as 600 hours of unlabelled speech - a quantity comparable to what infants can be exposed to during language acquisition.
On the Power and Limitations of Random Features for Understanding Neural Networks
Considering the one-hidden-layer example above, this corresponds to learning linear predictors over a fixed representation (chosen obliviously and randomly at initialization).
Video Timeline Modeling For News Story Understanding
In this paper, we present a novel problem, namely video timeline modeling.
DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision
Tam Nguyen, Maximilian Dax, Chaithanya Kumar Mummadi, Nhung Ngo, Thi Hoai Phuong Nguyen, Zhongyu Lou, Thomas Brox
Neural Information Processing Systems http://nips.cc/
Bayesian Learning of Sum-Product Networks
Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani
Neural Information Processing Systems http://nips.cc/