Built on Groundbreaking Research.
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.
Petuum: A New Platform for Distributed Machine Learning on Big Data
IEEE Transactions on Big Data, Volume 1, No. 2, Pages 49-67, 2015
Predicting Discharge Medications at Admission Time Based on Deep Learning
Towards Automated ICD Coding Using Deep Learning
Medical Diagnosis from Laboratory Tests by Combining Generative and Discriminative Learning
Effective Use of Bidirectional Language Modeling for Medical Named Entity Recognition
Proceedings of Machine Learning Research
On the Automatic Generation of Medical Imaging Reports
SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays
A New Look at the System, Algorithm and Theory Foundations of Distributed Machine Learning
KDD 2015 Tutorial
High Efficiency Systems for Distributed AI and ML at Scale
Strata+Hadoop World in Singapore, 2016