Major Petuum innovations include the parameter server architecture and theory, the stale-synchronous parallel bridging model, elastic resource scheduling technology, and managed network communication technology in high-performance distributed systems for ML and DL - as well as new ML and DL models and algorithms for actionable, human-level understanding and learning from images, videos and natural language.
IEEE Transactions on Big Data, Volume 1, No. 2, Pages 49-67, 2015
Engineering, Volume 2, No. 2, Pages 179-95, 2016
Symposium of Cloud Computing (SoCC 2018)
USENIX Annual Technical Conference (ATC 2017)
European Conference on Computer Systems (Eurosys 2016)
ACM Symposium on Cloud Computing (SOCC 2015), Best paper award!
Neural Information Processing Systems (NIPS 2013), Oral (top 5%)
Artificial Intelligence and Statistics (AISTATS 2016)
AAAI Conference on Artificial Intelligence (AAAI 2015)
Uncertainty in Artificial Intelligence (UAI 2016)
Petuum Healthcare Research is dedicated to developing state-of-the-art deep learning and machine learning techniques to aid clinical workflow and support clinical decision-making process.
Annual Meeting of the Association for Computational Linguistics (ACL 2016) | Outstanding Paper Award!
Annual Meeting of the Association for Computational Linguistics (ACL 2015) | Honorable Mention Recipient
Currently under submission
International Conference on Machine Learning (ICML 2016)
International Summer School on Deep Learning, Bilbao, Spain
Simons Institute for the Theory of Computing
Allen Institute for Artificial Intelligence
Strata+Hadoop World in Singapore, 2016
KDD 2015 Tutorial
ACML 2015, IJCAI 2015, Data Science Summit in San Francisco 2015, WSDM Winter School 2015, WWW 2015, Big Data Technology Conference in China 2014, ParLearning Workshop at IPDPS 2015