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07/02/2023
TensorGPT: Efficient Compression of the Embedding Layer in LLMs based on the Tensor-Train Decomposition
High-dimensional token embeddings underpin Large Language Models (LLMs),...
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05/23/2023
Amplitude-Independent Machine Learning for PPG through Visibility Graphs and Transfer Learning
Photoplethysmography (PPG) signals are omnipresent in wearable devices, ...
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05/09/2023
Convex Quaternion Optimization for Signal Processing: Theory and Applications
Convex optimization methods have been extensively used in the fields of ...
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05/09/2023
UAdam: Unified Adam-Type Algorithmic Framework for Non-Convex Stochastic Optimization
Adam-type algorithms have become a preferred choice for optimisation in ...
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03/23/2023
Graph Tensor Networks: An Intuitive Framework for Designing Large-Scale Neural Learning Systems on Multiple Domains
Despite the omnipresence of tensors and tensor operations in modern deep...
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12/22/2022
Rapid Extraction of Respiratory Waveforms from Photoplethysmography: A Deep Encoder Approach
Much of the information of breathing is contained within the photoplethy...
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01/24/2022
Pearl: Parallel Evolutionary and Reinforcement Learning Library
Reinforcement learning is increasingly finding success across domains wh...
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11/30/2021
HOTTBOX: Higher Order Tensor ToolBOX
HOTTBOX is a Python library for exploratory analysis and visualisation o...
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09/14/2021
An Apparatus for the Simulation of Breathing Disorders: Physically Meaningful Generation of Surrogate Data
Whilst debilitating breathing disorders, such as chronic obstructive pul...
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09/01/2021
Reducing Computational Complexity of Tensor Contractions via Tensor-Train Networks
There is a significant expansion in both volume and range of application...
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05/11/2021
Graph Theory for Metro Traffic Modelling
A unifying graph theoretic framework for the modelling of metro transpor...
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05/11/2021
Tensor-Train Recurrent Neural Networks for Interpretable Multi-Way Financial Forecasting
Recurrent Neural Networks (RNNs) represent the de facto standard machine...
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03/27/2021
Tensor Networks for Multi-Modal Non-Euclidean Data
Modern data sources are typically of large scale and multi-modal natures...
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10/25/2020
Multi-Graph Tensor Networks
The irregular and multi-modal nature of numerous modern data sources pos...
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09/18/2020
Recurrent Graph Tensor Networks
Recurrent Neural Networks (RNNs) are among the most successful machine l...
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08/10/2020
A Full Second-Order Analysis of the Widely Linear MVDR Beamformer for Noncircular Signals
A full performance analysis of the widely linear (WL) minimum variance d...
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07/27/2020
A Probabilistic Spectral Analysis of Multivariate Real-Valued Nonstationary Signals
A class of multivariate spectral representations for real-valued nonstat...
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02/26/2020
Tensor Decompositions in Deep Learning
The paper surveys the topic of tensor decompositions in modern machine l...
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01/27/2020
Supervised Learning for Non-Sequential Data with the Canonical Polyadic Decomposition
There has recently been increasing interest, both theoretical and practi...
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12/12/2019
Graph Theory and Metro Traffic Modelling
In this article we demonstrate how graph theory can be used to identify ...
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11/07/2019
A Statistically Identifiable Model for Tensor-Valued Gaussian Random Variables
Real-world signals typically span across multiple dimensions, that is, t...
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10/24/2019
Robust Principal Component Analysis Based On Maximum Correntropy Power Iterations
Principal component analysis (PCA) is recognised as a quintessential dat...
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10/12/2019
Portfolio Cuts: A Graph-Theoretic Framework to Diversification
Investment returns naturally reside on irregular domains, however, stand...
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09/12/2019
Unitary Shift Operators on a Graph
A unitary shift operator (GSO) for signals on a graph is introduced, whi...
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08/05/2019
A Unifying Analysis of Shift Operators on a Graph
The maximum entropy principle is employed to introduce a general class o...
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07/08/2019
Vertex-Frequency Graph Signal Processing
Graph signal processing deals with signals which are observed on an irre...
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03/14/2019
Tucker Tensor Layer in Fully Connected Neural Networks
We introduce the Tucker Tensor Layer (TTL), an alternative to the dense ...
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05/21/2018
A universal framework for learning based on the elliptical mixture model (EMM)
An increasing prominence of unbalanced and noisy data highlights the imp...
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11/22/2017
Hypergraph p-Laplacian: A Differential Geometry View
The graph Laplacian plays key roles in information processing of relatio...
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11/01/2017
Tensor Valued Common and Individual Feature Extraction: Multi-dimensional Perspective
A novel method for common and individual feature analysis from exceeding...
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04/28/2017
Simultaneous diagonalisation of the covariance and complementary covariance matrices in quaternion widely linear signal processing
Recent developments in quaternion-valued widely linear processing have e...
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04/28/2017
Diagonalisation of covariance matrices in quaternion widely linear signal processing
Recent developments in quaternion-valued widely linear processing have i...
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01/03/2017
Automatic sleep monitoring using ear-EEG
The monitoring of sleep patterns without patient's inconvenience or invo...
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03/08/2016
Frequency estimation in three-phase power systems with harmonic contamination: A multistage quaternion Kalman filtering approach
Motivated by the need for accurate frequency information, a novel algori...
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07/05/2012
