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).