| 9:00-10:00 | Keynote talk III (invited): William Cohen (Carnegie Mellon University) | |
| 10:00-10:20 | Coffee break | |
| 10:20-11:35 | Session 2: Speech & Language | |
| Andrea F. Daniele (Toyota Technological Institute at Chicago), Mohit Bansal (University of North Carolina at Chapel Hill) and Matthew Walter (Toyota Technological Institute at Chicago) | Navigational Instruction Generation as Inverse Reinforcement Learning with Neural Machine Translation |
| Shubham Toshniwal (Toyota Technological Institute at Chicago), Hao Tang (Toyota Technological Institute at Chicago), Liang Lu (Toyota Technological Institute at Chicago) and Karen Livescu (Toyota Technological Institute at Chicago) | Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition |
| John Wieting (Toyota Technological Institute at Chicago), Mohit Bansal(University of North Carolina Chapel Hill), Kevin Gimpel (Toyota Technological Institute at Chicago) and Karen Livescu (Toyota Technological Institute at Chicago) | Neural Architectures for Modeling Compositionality in Natural Language |
| 11:35-13:30 | Lunch break | |
| 13:30-14:30 | Keynote talk IV: Jun-ichi Tsujii (National Institute of Advanced Industrial Science and Technology) | |
| 14:30-15:30 | Poster Session | |
| Matthew J. Holland (Nara Institute of Science and Technology) and Kazushi Ikeda (Nara Institute of Science and Technology) | Memory, Bias, and Variance Reduction |
| Zhenghang Cui (University of Tokyo), Issei Sato (University of Tokyo/RIKEN) and Masashi Sugiyama (University of Tokyo/RIKEN) | Stochastic Divergence Minimization for Biterm Topic Model |
| Yin Jun Phua (Tokyo Institute of Technology), Sophie Tourret (National Institute of Informatics) and Katsumi Inoue (National Institute of Informatics, Tokyo Institute of Technology) | Learning Logic Program Representation From Delayed Interpretation Transition Using Recurrent Neural Networks |
| Haiping Huang (RIKEN), Alireza Goudarzi (RIKEN) and Taro Toyoizumi (RIKEN) | Combining DropConnect and Feedback Alignment for Efficient Regularization in Deep Networks |
| Jen-Tzung Chien (National Chiao Tung University) and Ching-Wei Huang (National Chiao Tung University) | Variational and Adversarial Domain Adaptation |
| Miki Ueno (Toyohashi University of Technology) | Comic Book Interpretation based on Deep Neural Networks |
| Nicholas Altieri (University of California Berkeley), Sherdil Niyaz (University of California Berkeley), Samee Ibraheem (University of California Berkeley) and John Denero (University of California Berkeley) | Improved Word and Symbol Embedding for Part-of-Speech Tagging |
| Marc Evrard (Toyota Technological Institute), Makoto Miwa (Toyota Technological Institute) and Yutaka Sasaki (Toyota Technological Institute) | TTI's Approaches to Symbolic-Neural Learning (*) |
| 15:30-17:35 | Session 3: New Learning Approaches | |
| Han Bao (University of Tokyo), Masashi Sugiyama (The University of Tokyo/RIKEN), Issei Sato (University of Tokyo/RIKEN) and Tomoya Sakai(University of Tokyo/RIKEN) | Risk Minimization Framework for Multiple Instance Learning from Positive and Unlabeled Bags |
| Tomoya Sakai(University of Tokyo/RIKEN), Marthinus Christoffel Du Plessis (University of Tokyo), Gang Niu (University of Tokyo) and Masashi Sugiyama (University of Tokyo/RIKEN) | Semi-Supervised Classification based on Positive-Unlabeled Classification |
| Tetsuya Hada (Osaka University/RIKEN), Akifumi Okuno (Kyoto University/RIKEN) and Hidetoshi Shimodaira (Kyoto University/RIKEN) | Deep Multi-view Representation Learning Based on Adaptive Weighted Similarity |
| Makoto Yamada (RIKEN/JST/PRESTO), Koh Takeuchi (NTT CS Labs), Tomoharu Iwata (NTT CS Labs), John Shawe-Taylor (University College London) and Samuel Kaski (Aalto University) | Localized Lasso for High-Dimensional Regression |
| Tim Rocktäschel (University of Oxford) and Sebastian Riedel (University College London) | Neural Theorem Provers |
| 17:40-17:50 | Closing | |