Just as a quick disclaimer, this post is about my personal experience and opinions at NIPS 2017, and I'm not an AI researcher, I work as a data scientist in the industry. For a more technical summary of the talks and papers presented, you may want to check this document by David Abel.
Deep learning rigor and interpretability
- Understand how learning works, and replicate it based on this understanding
- Focus on results, no matter if it's at the cost of poor understanding
RL was the last of the main topics that kept repeating during the whole NIPS, if I'm not missing any. Both based on the classic q-learning, or by using deep learning representations.
About the conference
- Near to a main airport, so I could fly directly from London
- Good temperature
- Many hotels nearby
- English speaking country
- The only problem with the location was that people from several countries (e.g. Iran) were banned from attending, as the organizers mentioned in the home page of the conference
- I found it difficult to know what to expect about food. I think in all previous conference I attended (and they are not few), breakfast and lunch was provided. At #NIPS it was advertised in the schedule that breakfast wasn't offered first time in the morning, no other mention. Then, breakfast was provided later in the morning (one day the !(https://2.bp.blogspot.com/-sytt8-nPHl8/WjWYACiZGuI/AAAAAAAAymo/FMSCxkkEsTgxLw20XjnvuJH6iJyR9Ux2gCLcBGAs/s320/IMG_20171205_112058.jpg)