• Learning Deep Architectures for AI
• Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
• Towards Neural Network-based Reasoning
• Large Language Models in Machine Translation
• A Few Useful Things to Know About Machine Learning
• Thinking in Parallel: Some Basic Data-Parallel Algorithms and Techniques
• Spectral Analysis for Billion-Scale Graphs: Discoveries and Implementation
• Distributed Algorithms for Topic Models
• Learning Multiple Layers of Features from Tiny Images
• Learning using Large Datasets
• Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
• Intriguing properties of neural networks
• Training recurrent networks online without backtracking
• Pattern Recognition and Machine Learning
• PEGASUS: A Peta-Scale Graph Mining System - Implementation and Observations
• Parallel Spectral Clustering in Distributed Systems