| Christopher Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Mohammad Norouzi, Andriy Mnih, Arnaud Doucet and Yee Whye Teh. |
Filtering Variational Objectives |
| George Tucker, Andriy Mnih, Chris J. Maddison, Dieterich Lawson and Jascha Sohl-Dickstein. |
REINFORCing Concrete with REBAR |
| Rémi Leblond, Jean-Baptiste Alayrac, Anton Osokin and Simon Lacoste-Julien. |
SEARNN : Training RNNs with global-local losses |
| David Belanger and Andrew McCallum. |
Randomized SPENs for Multi-Modal Prediction |
| Po-Sen Huang, Chong Wang, Dengyong Zhou and Li Deng. |
Toward Neural Phrase-based Machine Translation |
| Dung Thai, Shikhar Murty, Trapit Bansal, Luke Vilnis, David Belanger and Andrew McCallum. |
Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling |
| Wu Lin, Mohammad Emtiyaz Khan, Nicolas Hubacher and Didrik Nielsen. |
Natural-Gradient Stochastic Variational Inference for Non-Conjugate Structured Variational Autoencoder |
| Jason Naradowsky and Sebastian Riedel. |
Modeling Exclusion with a Differentiable Factor Graph Constraint |
| Yinchong Yang, Volker Tresp and Peter Fasching. |
Modeling Clinical Decisions with Multinomial Hierarchical Classification |
| Stephan Zheng, Rose Yu and Yan Liu. |
Learning Chaotic Dynamics using Tensor Recurrent Neural Networks |
| Dan Goldwasser, Jennifer Neville, Yi-Yu Lai and Chang Li. |
Joint Embedding Models for Textual and Social Analysis |
| Xiang Li, Luke Vilnis and Andrew McCallum. |
Improved Representation Learning for Predicting Commonsense Ontologies |
| Pablo Rozas Larraondo, Inaki Inza and Jose Antonio Lozano. |
Automating weather forecasts based on convolutional networks |
| Hao Liu, Xinyi Yang and Zenglin Xu. |
Structured Neural Turing Machine |
| Joel Ruben Antony Moniz and Christopher Pal. |
Deep Convolutional Networks with Non-convolutional Recurrent Memory for Structured Prediction |
| Xinyi Yang, Hao Liu and Zenglin Xu. |
Variational Structured Stochastic Network |
| Lev Faivishevsky and Amitai Armon. |
Deep structured modeling of deep learning training convergence with application to hyperparameter optimization |
| Heejin Choi and Karl Stratos |
Handling Large Structural Costs in Neural Networks with Slack Rescaling |