Microsoft researchers enable secure data exchange in the cloud
By John Roach, Writer, Microsoft Research In the future, machine learning algorithms may examine our genomes to determine our susceptibility to maladies such as heart disease and cancer. Between now and then, computer scientists need…
Inference Remapping for Vehicular Analytics
Microsoft NLP researchers converge at ACL 2016, edging ever closer to human-like conversational experiences
By Bill Dolan, Principal Researcher, Microsoft Research This year, the annual meeting of the Association for Computational Linguistics (ACL) will be held in Berlin, Germany, August 7-12, 2016, at Humboldt University. ACL is the premier…
Generating Natural Questions About an Image
Distributed DNN platform
DNN is a really important and practical machine learning capability, this project focuses on finding solution for distributing the DNN training on a cluster of machines based on our parameter server framework. The research in…
Model Scheduling For Super Large Scale Model Training
Machine learning in this big data era is facing two challenges, one is big data, the other is big model (one machine cannot hold the entire model in runtime). In distributed machine learning, people has…
DMTK
DMTK is an open source project running in our group to share our recent research output on distributed machine learning with open source community. It contains our Multiverso parameter server platform and many of our…
Click prediction in sponsored search
Click prediction is one of the major technical parts in sponsored search which dramatically affect the overall revenue of search engine. In this project we have proposed quite a few new method and aspects to…
LightLDA
LightLDA is a distributed system for large scale topic modeling. It implements a distributed sampler that enables very large data sizes and models. LightLDA improves sampling throughput and convergence speed via a fast O(1) metropolis-Hastings…