This is a partial list of papers we will study in the second half of CS380C. 


Using machine learning in programming systems


       Machine learning in compiler optimization  Wang and O’Boyle, arXiv:1805.03441.


       Code2vec: Learning distributed representations of code Alon et al., POPL 2019.


       Node2vec:Embeddings for graph data Grover and Leskovec, KDD 2016.


       Learning to represent programs with graphs Allamanis et al., ICLR 2018.


       SemCluster: Clustering of Programming Assignments based on Quantitative Semantic Features Perry et al. PLDI 2019


       Proactive control of approximate programs Xin Sui et al., ASPLOS 2016.



High-performance implementations of machine-learning algorithms


       TensorFlow: A System for Large-scale Machine Learning Abadi et al. OSDI 2016.


MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems Tianqi Chen et al., NIPS 2016.


       Distributed Word2Vec using Graph Analytics Frameworks Gill et al. (arxiv).