This paper presents anewUNIfied pre-trainedLanguageModel (UNILM)that can be fine-tuned for both natural language understanding and generation tasks.

The discovery likely dates back to the continent's gold rushes. Breakthroughs, discoveries, and DIY tips sent six days a week. A metal detector hobbyist discovered a centuries' old coin while scouring an abandoned sports field--and the coin is especially rare for the area. In the southern Australian province of Victoria, treasure hunting enthusiast Angus James recently spotted a well-preserved 100 Mon Tenpō Tsūhō, a 19th century Japanese coin likely deposited during Australia's decades' long gold rush. "You never know what you'll find next," James posted to social media on January 25th, along with photos of his recent haul.

Neural Information Processing Systems http://nips.cc/

This allows us to derive an upper bound on the susceptibility of explanations to manipulations.

Existing deep methods overlook those appearance and geometric differences, and instead use a brute force training procedure, leading to inferior performance.

Wedemonstrate that our visualization provides intuitive, detailed summaries of the learning dynamics beyond simple global measures (i.e., validation loss and accuracy), without the need to access validation data. Furthermore, M-PHATE better captures both the dynamics and community structure of the hidden units as compared to visualization based on standard dimensionality reduction methods (e.g., ISOMAP,t-SNE).

A popular trend in recent years is using symbolic planning models with reinforcement learning (RL) algorithms.