726 citations · 2.2k across the 66 of their papers we have counts for
4 papers · 1 filter
Stacked Kernel Network
Shuai Zhang, Jianxin Li, Pengtao Xie +4
Kernel methods are powerful tools to capture nonlinear patterns behind data. They implicitly learn high (even infinite) dimensional nonlinear features in the Reproducing Kernel Hil…
Strategies and Principles of Distributed Machine Learning on Big Data
Eric P. Xing, Qirong Ho, Pengtao Xie +1
The rise of Big Data has led to new demands for Machine Learning (ML) systems to learn complex models with millions to billions of parameters, that promise adequate capacity to dig…
Distributed Training of Deep Neural Networks with Theoretical Analysis: Under SSP Setting
Abhimanu Kumar, Pengtao Xie, Junming Yin +1
We propose a distributed approach to train deep neural networks (DNNs), which has guaranteed convergence theoretically and great scalability empirically: close to 6 times faster on…
Petuum: A New Platform for Distributed Machine Learning on Big Data
Eric P. Xing, Qirong Ho, Wei Dai +7
What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big D…