Background
oPRO.ai is built on years of groundbreaking work on machine learning and distributed computing.
Publications
Systems
oPRO.ai: A New Platform for Distributed Machine Learning on Big Data
IEEE Transactions on Big Data
Orpheus: Efficient Distributed Machine Learning via System and Algorithm Co-design
Symposium of Cloud Computing (SoCC)
Poseidon: An Efficient Communication Interface for Distributed Deep Learning on GPU Clusters
USENIX Annual Technical Conference
STRADS: A Distributed Framework for Scheduled Model Parallel Machine Learning
European Conference on Computer Systems (EuroSys)
Managed Communication and Consistency for Fast Data-Parallel Iterative Analytics
ACM Symposium on Cloud Computing (SOCC), Best paper award
More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server
Neural Information Processing Systems (NeurIPS), Oral (top 5%)
On Model Parallelization and Scheduling Strategies for Distributed Machine Learning
Neural Information Processing Systems (NeurIPS)
Theory
On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System
Artificial Intelligence and Statistics (AISTATS)
Analysis of High-Performance Distributed ML at Scale Through Parameter Server Consistency Models
AAAI Conference on Artificial Intelligence (AAAI)
Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting
Uncertainty in Artificial Intelligence (UAI)
Other Applications
Harnessing Deep Neural Networks with Logic Rules
Annual Meeting of the Association for Computational Linguistics (ACL), Outstanding Paper Award
Learning Answer-Entailing Structures for Machine Comprehension
Annual Meeting of the Association for Computational Linguistics (ACL), Honorable Mention Recipient
ZM-Net: Real-time Zero-shot Image Manipulation Network
Currently under submission
Diversity-Promoting Bayesian Learning of Latent Variable Models
International Conference on Machine Learning (ICML)
Science Question Answering Using Instructional Materials
Annual Meeting of the Association for Computational Linguistics (ACL)
Learning Concept Taxonomies from Multi-Modal Data
Annual Meeting of the Association for Computational Linguistics (ACL)
Grounding Topic Models with Knowledge Bases
International Joint Conference on Artificial Intelligence (IJCAI)
Presentations
A Statistical Machine Learning Perspective of Deep Learning: Algorithm, Theory, Scalable Computing
International Summer School on Deep Learning, Bilbao, Spain
System and Algorithm Co-Design, Theory and Practice, for Distributed Machine Learning
Simons Institute for the Theory of Computing
High Efficiency Systems for Distributed AI and ML at Scale
Strata+Hadoop World in Singapore