no code implementations • 16 Apr 2021 • Gary Phua, Shaowei Lin, Dario Poletti
We used a modified version of the negative sampling objective for our context words, modelling the context embeddings as a Taylor series of rate matrices.
no code implementations • 8 Mar 2020 • Zhangsheng Lai, Aik Beng Ng, Liang Ze Wong, Simon See, Shaowei Lin
Reasoning over knowledge graphs is traditionally built upon a hierarchy of languages in the Semantic Web Stack.
no code implementations • 25 Nov 2019 • Zuozhu Liu, Thiparat Chotibut, Christopher Hillar, Shaowei Lin
Motivated by the celebrated discrete-time model of nervous activity outlined by McCulloch and Pitts in 1943, we propose a novel continuous-time model, the McCulloch-Pitts network (MPN), for sequence learning in spiking neural networks.
no code implementations • 21 Nov 2017 • Zuozhu Liu, Tony Q. S. Quek, Shaowei Lin
The quest for biologically plausible deep learning is driven, not just by the desire to explain experimentally-observed properties of biological neural networks, but also by the hope of discovering more efficient methods for training artificial networks.
no code implementations • 23 Feb 2016 • Mohammad Abu Alsheikh, Dusit Niyato, Shaowei Lin, Hwee-Pink Tan, Zhu Han
The proliferation of mobile devices, such as smartphones and Internet of Things (IoT) gadgets, results in the recent mobile big data (MBD) era.
no code implementations • 15 Nov 2015 • Mohammad Abu Alsheikh, Ahmed Selim, Dusit Niyato, Linda Doyle, Shaowei Lin, Hwee-Pink Tan
Despite the widespread installation of accelerometers in almost all mobile phones and wearable devices, activity recognition using accelerometers is still immature due to the poor recognition accuracy of existing recognition methods and the scarcity of labeled training data.
no code implementations • 2 Aug 2015 • Mohammad Abu Alsheikh, Shaowei Lin, Hwee-Pink Tan, Dusit Niyato
Our contributions that address three major issues include: 1) an effective method that extracts population sparsity of the data, 2) a sparsity ratio guarantee scheme, and 3) a customized learning algorithm of the sparsifying dictionary.
no code implementations • 29 Dec 2014 • Mathias Drton, Shaowei Lin, Luca Weihs, Piotr Zwiernik
We clarify how in this case real log-canonical thresholds can be computed using polyhedral geometry, and we show how to apply the general theory to the Laplace integrals associated with Gaussian latent tree and forest models.
no code implementations • 18 May 2014 • Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato, Hwee-Pink Tan
In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs).