Derrick

https://arxiv.org/abs/1702.02390 # Abstract - this model uses rnn + feed-forward convolutional architecture - author claims this model has - fast train convergence - handles long sequences - avoid major difficulties...

Diversity Is All You Need: Learning Skills without a Reward Function

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https://arxiv.org/abs/1802.06070 # Abstract - Learn **skills** by maximizing information using maximum entropy policy - Train typical reinforcement learning with best **skill** after unsupervised learning # 1. Introduction - **Skill** is...

https://arxiv.org/abs/1711.02281 # Abstract Features - Non-Autoregressive (means output selves doesn't have dependency) - Parallel outputs How - Knowledge distillation - Input token fertilities - Policy Gradient # 1. Introduction Paper...

# Convolution Sequence to Sequence Learning aka Fairseq https://arxiv.org/pdf/1705.03122.pdf # 3. A Convolutional Architecture ## 3.1. Position Embeddings  P for position vector  e for embedding ### See also...

https://arxiv.org/abs/1802.06006 Paper from Baidu Research # Abstract Paper will do - Speaker adaption - fine-tuning a multi-speaker generative model - Speaker encoding - infer speaker embedding which will be used...

https://arxiv.org/abs/1802.06842 **Terms** - **Triple**: Tuple of (subject, predicate, object) - **Knowledge Base**: embedding of knowledge (this paper uses TransE) # Abstract - This paper uses part-of-speech copy attention mechanism (this...

https://arxiv.org/abs/1704.01444 paper from OpenAI # Summary This paper shows that **"Your training dataset should cover your target tasks"** by using [mLSTM](https://arxiv.org/abs/1609.07959) and ***Sentiment Analysis*** # Abstract - When given sufficient...

https://arxiv.org/abs/1610.10099 aka ByteNet paper from Deepmind **Notations** - **s**: source - **t**: target # Abstract Features - (model feature) stacking decoder on top of encoder - (training feature) decoder using...

https://arxiv.org/abs/1803.01271 this paper introduces Temporal Convolutional Networks (aka TCN) # Summary Showing empirical general convolutional Model(Temporal Convolutional Networks; **TCN**) are better than RNNs in several tasks. # Abstract - Convolutional...

https://arxiv.org/abs/1611.00179 paper from USTC, PKU, Microsoft Research (NIPS 2016) # Summary ## Model 1. Prepare 2 agents **LM_{a,b}** which learned languages(en,fr; ***WMT14***) that outputs log probability 2. 2 translation models...