4 citations · 14 across the 9 of their papers we have counts for
10 papers
Asynchronous Decentralized Distributed Training of Acoustic Models
Xiaodong Cui, Wei Zhang, Abdullah Kayi +5
Large-scale distributed training of deep acoustic models plays an important role in today's high-performance automatic speech recognition (ASR). In this paper we investigate a vari…
CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks
Ruchir Puri, David S. Kung, Geert Janssen +14
Over the last several decades, software has been woven into the fabric of every aspect of our society. As software development surges and code infrastructure of enterprise applicat…
Large Scale Neural Architecture Search with Polyharmonic Splines
Ulrich Finkler, Michele Merler, Rameswar Panda +8
Neural Architecture Search (NAS) is a powerful tool to automatically design deep neural networks for many tasks, including image classification. Due to the significant computationa…
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search
Rameswar Panda, Michele Merler, Mayoore Jaiswal +8
Neural Architecture Search (NAS) is an open and challenging problem in machine learning. While NAS offers great promise, the prohibitive computational demand of most of the existin…
Map Generation from Large Scale Incomplete and Inaccurate Data Labels
Rui Zhang, Conrad Albrecht, Wei Zhang +4
Accurately and globally mapping human infrastructure is an important and challenging task with applications in routing, regulation compliance monitoring, and natural disaster respo…
Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition
Xiaodong Cui, Wei Zhang, Ulrich Finkler +3
The past decade has witnessed great progress in Automatic Speech Recognition (ASR) due to advances in deep learning. The improvements in performance can be attributed to both impro…
Improving Efficiency in Large-Scale Decentralized Distributed Training
Wei Zhang, Xiaodong Cui, Abdullah Kayi +9
Decentralized Parallel SGD (D-PSGD) and its asynchronous variant Asynchronous Parallel SGD (AD-PSGD) is a family of distributed learning algorithms that have been demonstrated to p…
A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition
Wei Zhang, Xiaodong Cui, Ulrich Finkler +6
Modern Automatic Speech Recognition (ASR) systems rely on distributed deep learning to for quick training completion. To enable efficient distributed training, it is imperative tha…
Distributed Deep Learning Strategies For Automatic Speech Recognition
Wei Zhang, Xiaodong Cui, Ulrich Finkler +4
In this paper, we propose and investigate a variety of distributed deep learning strategies for automatic speech recognition (ASR) and evaluate them with a state-of-the-art Long sh…
PowerAI DDL
Minsik Cho, Ulrich Finkler, Sameer Kumar +3
As deep neural networks become more complex and input datasets grow larger, it can take days or even weeks to train a deep neural network to the desired accuracy. Therefore, distri…