Search Results for author: Shaowei Lin

Found 9 papers, 0 papers with code

Word2rate: training and evaluating multiple word embeddings as statistical transitions

no code implementations16 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.

Sentiment Analysis Translation +1

Dependently Typed Knowledge Graphs

no code implementations8 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.

Knowledge Graphs

Biologically Plausible Sequence Learning with Spiking Neural Networks

no code implementations25 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.

Variational Probability Flow for Biologically Plausible Training of Deep Neural Networks

no code implementations21 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.

Biologically-plausible Training

Mobile Big Data Analytics Using Deep Learning and Apache Spark

no code implementations23 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.

Activity Recognition Deep Learning

Deep Activity Recognition Models with Triaxial Accelerometers

no code implementations15 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.

Human Activity Recognition Temporal Sequences

Toward a Robust Sparse Data Representation for Wireless Sensor Networks

no code implementations2 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.

Compressive Sensing

Marginal likelihood and model selection for Gaussian latent tree and forest models

no code implementations29 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.

Bayesian Inference Model Selection

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

no code implementations18 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).

BIG-bench Machine Learning

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