Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Morphologically-Aware Vocabulary Reduction Of Word Embeddings, Chong Cher Chia, Maksim Tkachenko, Hady Wirawan Lauw
Morphologically-Aware Vocabulary Reduction Of Word Embeddings, Chong Cher Chia, Maksim Tkachenko, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
We propose SubText, a compression mechanism via vocabulary reduction. The crux is to judiciously select a subset of word embeddings which support the reconstruction of the remaining word embeddings based on their form alone. The proposed algorithm considers the preservation of the original embeddings, as well as a word’s relationship to other words that are morphologically or semantically similar. Comprehensive evaluation of the compressed vocabulary reveals SubText’s efficacy on diverse tasks over traditional vocabulary reduction techniques, as validated on English, as well as a collection of inflected languages.
D-Pruner: Filter-Based Pruning Method For Deep Convolutional Neural Network, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan
D-Pruner: Filter-Based Pruning Method For Deep Convolutional Neural Network, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
The emergence of augmented reality devices such as Google Glass and Microsoft Hololens has opened up a new class of vision sensing applications. Those applications often require the ability to continuously capture and analyze contextual information from video streams. They often adopt various deep learning algorithms such as convolutional neural networks (CNN) to achieve high recognition accuracy while facing severe challenges to run computationally intensive deep learning algorithms on resource-constrained mobile devices. In this paper, we propose and explore a new class of compression technique called D-Pruner to efficiently prune redundant parameters within a CNN model to run the model …
D-Pruner: Filter-Based Pruning Method For Deep Convolutional Neural Network, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan
D-Pruner: Filter-Based Pruning Method For Deep Convolutional Neural Network, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
The emergence of augmented reality devices such as Google Glass and Microsoft Hololens has opened up a new class of vision sensing applications. Those applications often require the ability to continuously capture and analyze contextual information from video streams. They often adopt various deep learning algorithms such as convolutional neural networks (CNN) to achieve high recognition accuracy while facing severe challenges to run computationally intensive deep learning algorithms on resource-constrained mobile devices. In this paper, we propose and explore a new class of compression technique called D-Pruner to efficiently prune redundant parameters within a CNN model to run the model …
A Novel Representation And Compression For Queries On Trajectories In Road Networks, Xiaochun Yang, Bin Wang, Kai Yang, Chengfei Liu, Baihua Zheng
A Novel Representation And Compression For Queries On Trajectories In Road Networks, Xiaochun Yang, Bin Wang, Kai Yang, Chengfei Liu, Baihua Zheng
Research Collection School Of Computing and Information Systems
Recording and querying time-stamped trajectories incurs high cost of data storage and computing. In this paper, we explore several characteristics of the trajectories in road mbox{networks}, which have motivated the idea of coding trajectories by associating timestamps with relative spatial path and locations. Such a representation contains large number of duplicate information to achieve a lower entropy compared with the existing representations, thereby drastically cutting the storage cost. We propose several techniques to compress spatial path and locations separately, which can support fast positioning and achieve better compression ratio. For locations, we propose two novel encoding schemes such that the …