techxiv
Spam Fighting @Scale 2016 
What matters to you, matters to us. - Open population datasets and open challenges
#Exploration: A study of count-based exploration for deep reinforcement learning - OpenAI and Microsoft
- On the quantitative analysis of decoder-based generative models
Redux-Doghouse: Creating reusable React-Redux components through scoping - Redux-Doghouse: Creating reusable React-Redux components through scoping
- A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models
- Facebook demonstrates record-breaking data rate using millimeter-wave technology
- RL²: Fast reinforcement learning via slow reinforcement learning
- Introducing Backpack: Our second-generation modular open switch
- Accelerating innovation and powering new experiences with AI
- Delivering real-time AI in the palm of your hand
- Variational lossy autoencoder
A solution to the ppx versioning problem - Introducing Community Cellular Manager: A management and deployment suite for small-scale cellular networks
- Extensions and limitations of the neural GPU
- An open approach for switching, routing, and transport
- Networking @Scale Boston