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Motivated by vision-based reinforcement learning (RL) problems, in particular Atari games from the recent benchmark Aracade Learning Environment (ALE), we consider spatio-temporal prediction problems… (More)
The combination of modern Reinforcement Learning and Deep Learning approaches holds the promise of making significant progress on challenging applications requiring both rich perception and… (More)
- Shuohang Wang, Mo Yu, +7 authors Jing Jiang
- AAAI
- 2018
In recent years researchers have achieved considerable success applying neural network methods to question answering (QA). These approaches have achieved state of the art results in simplified… (More)
- Cheng Li, Jiaqi Ma, Xiaoxiao Guo, Qiaozhu Mei
- WWW
- 2017
Information cascades, effectively facilitated by most social network platforms, are recognized as a major factor in almost every social success and disaster in these networks. Can cascades be… (More)
- Shiyu Chang, Yonghui Zhang, +7 authors Thomas S. Huang
- NIPS
- 2017
Learning with recurrent neural networks (RNNs) on long sequences is a notoriously difficult task. There are three major challenges: 1) complex dependencies, 2) vanishing and exploding gradients, and… (More)
- Shuohang Wang, Mo Yu, +7 authors Murray Campbell
- ArXiv
- 2017
A popular recent approach to answering open-domain questions is to first search for question-related passages and then apply reading comprehension models to extract answers. Existing methods usually… (More)
- Xiaoxiao Guo, Wei Li, Francesco Iorio
- KDD
- 2016
In aerodynamics related design, analysis and optimization problems, flow fields are simulated using computational fluid dynamics (CFD) solvers. However, CFD simulation is usually a computationally… (More)
Options in reinforcement learning allow agents to hierarchically decompose a task into subtasks, having the potential to speed up learning and planning. However, autonomously learning effective sets… (More)
A key goal of research in conversational systems is to train an interactive agent to help a user with a task. Human conversation, however, is notoriously incomplete, ambiguous, and full of extraneous… (More)
- Shuohang Wang, Mo Yu, +7 authors Jing Jiang
- ArXiv
- 2017
In recent years researchers have achieved considerable success applying neural network methods to question answering (QA). These approaches have achieved state of the art results in simplified… (More)