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).