Machine Translation
Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems
Mrinmaya Sachan, Kumar Avinava Dubey, Tom M. Mitchell, Dan Roth, Eric P. Xing
Neural Information Processing Systems http://nips.cc/
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
Jiasen Lu, Dhruv Batra, Devi Parikh, Stefan Lee
Neural Information Processing Systems http://nips.cc/
Unified Language Model Pre-training for Natural Language Understanding and Generation
Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, Hsiao-Wuen Hon
This paper presents anewUNIfied pre-trainedLanguageModel (UNILM)that can be fine-tuned for both natural language understanding and generation tasks.
Cross-lingual Language Model Pretraining
Alexis CONNEAU, Guillaume Lample
Neural Information Processing Systems http://nips.cc/
Post: Device Placement with Cross-Entropy Minimization and Proximal Policy Optimization
Yuanxiang Gao, Li Chen, Baochun Li
Neural Information Processing Systems http://nips.cc/
Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot Learning
yunlong yu, Zhong Ji, Yanwei Fu, Jichang Guo, Yanwei Pang, Zhongfei (Mark) Zhang
Neural Information Processing Systems http://nips.cc/
Adaptive Methods for Nonconvex Optimization
Manzil Zaheer, Sashank Reddi, Devendra Sachan, Satyen Kale, Sanjiv Kumar
The first prominent algorithms in this line of research isADAGRAD [7,22], which uses a per-dimension learning rate based on squared pastgradients.ADAGRADachievedsignificant performance gainsincomparison toSGDwhenthe gradientsaresparse.
Inherent Tradeoffs in Learning Fair Representations
Neural Information Processing Systems http://nips.cc/
From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces Peter Shaw
Much of the previous work towards digital agents for graphical user interfaces (GUIs) has relied on text-based representations (derived from HTML or other structured data sources), which are not always readily available.