Queen Mary University of London

research

∙ 12/14/2021

Graph Kernel Neural Networks

The convolution operator at the core of many modern neural architectures...

Luca Cosmo, et al. ∙

research

∙ 01/27/2019

Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study

Background: The trend towards large-scale studies including population i...

Robert Robinson, et al. ∙

research

∙ 09/10/2019

Privacy-Preserving Bandits

Contextual bandit algorithms (CBAs) often rely on personal data to provi...

Mohammad Malekzadeh, et al. ∙

research

∙ 11/14/2019

Privacy and Utility Preserving Sensor-Data Transformations

Sensitive inferences and user re-identification are major threats to pri...

Mohammad Malekzadeh, et al. ∙

research

∙ 04/20/2022

Federated Learning for Energy-limited Wireless Networks: A Partial Model Aggregation Approach

The limited communication resources, e.g., bandwidth and energy, and dat...

Zhixiong Chen, et al. ∙

research

∙ 01/30/2020

Conditioning Autoencoder Latent Spaces for Real-Time Timbre Interpolation and Synthesis

We compare standard autoencoder topologies' performances for timbre gene...

Joseph T Colonel, et al. ∙

research

∙ 01/03/2019

Efficient Evolutionary Methods for Game Agent Optimisation: Model-Based is Best

This paper introduces a simple and fast variant of Planet Wars as a test...

Simon M. Lucas, et al. ∙

research

∙ 01/13/2019

GAN-based Virtual Re-Staining: A Promising Solution for Whole Slide Image Analysis

Histopathological cancer diagnosis is based on visual examination of sta...

Zhaoyang Xu, et al. ∙

research

∙ 01/14/2022

Formula graph self-attention network for representation-domain independent materials discovery

The success of machine learning (ML) in materials property prediction de...

Achintha Ihalage, et al. ∙

research

∙ 04/14/2022

Methodical Advice Collection and Reuse in Deep Reinforcement Learning

Reinforcement learning (RL) has shown great success in solving many chal...

Sahir, et al. ∙

research

∙ 03/09/2020

Knowledge distillation via adaptive instance normalization

This paper addresses the problem of model compression via knowledge dist...

Jing Yang, et al. ∙

research

∙ 03/06/2022

HEAR 2021: Holistic Evaluation of Audio Representations

What audio embedding approach generalizes best to a wide range of downst...

Joseph Turian, et al. ∙

research

∙ 05/28/2022

Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning

Recent progress in deep model-based reinforcement learning allows agents...

Remo Sasso, et al. ∙

research

∙ 07/19/2022

Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications

Communication systems to date primarily aim at reliably communicating bi...

Deniz Gündüz, et al. ∙

research

∙ 01/24/2020

Stacked Auto Encoder Based Deep Reinforcement Learning for Online Resource Scheduling in Large-Scale MEC Networks

An online resource scheduling framework is proposed for minimizing the s...

Feibo Jiang, et al. ∙

research

∙ 09/05/2021

Timbre Transfer with Variational Auto Encoding and Cycle-Consistent Adversarial Networks

This research project investigates the application of deep learning to t...

Russell Sammut Bonnici, et al. ∙

research

∙ 08/27/2019

Intra-Camera Supervised Person Re-Identification: A New Benchmark

Existing person re-identification (re-id) methods rely mostly on a large...

Xiangping Zhu, et al. ∙

research

∙ 09/27/2021

WarpedGANSpace: Finding non-linear RBF paths in GAN latent space

This work addresses the problem of discovering, in an unsupervised manne...

Christos Tzelepis, et al. ∙

research

∙ 05/12/2022

Towards Robust Unsupervised Disentanglement of Sequential Data – A Case Study Using Music Audio

Disentangled sequential autoencoders (DSAEs) represent a class of probab...

Yin-Jyun Luo, et al. ∙

research

∙ 05/13/2022

Knowledge Distillation Meets Open-Set Semi-Supervised Learning

Existing knowledge distillation methods mostly focus on distillation of ...

Jing Yang, et al. ∙

research

∙ 06/06/2018

Deep Reinforcement Learning for General Video Game AI

The General Video Game AI (GVGAI) competition and its associated softwar...

Ruben Rodriguez Torrado, et al. ∙

research

∙ 04/14/2020

A Transfer Learning approach to Heatmap Regression for Action Unit intensity estimation

Action Units (AUs) are geometrically-based atomic facial muscle movement...

Ioanna Ntinou, et al. ∙

research

∙ 12/30/2021

Semantic Communications: Principles and Challenges

Semantic communication, regarded as the breakthrough beyond Shannon para...

Zhijin Qin, et al. ∙

research

∙ 07/16/2021

DoReMi: First glance at a universal OMR dataset

The main challenges of Optical Music Recognition (OMR) come from the nat...

Elona Shatri, et al. ∙

research

∙ 07/30/2021

DadaGP: A Dataset of Tokenized GuitarPro Songs for Sequence Models

Originating in the Renaissance and burgeoning in the digital era, tablat...

Pedro Sarmento, et al. ∙

research

∙ 01/31/2019

Episodic Training for Domain Generalization

Domain generalization (DG) is the challenging and topical problem of lea...

Da Li, et al. ∙

research

∙ 04/03/2019

Rinascimento: Optimising Statistical Forward Planning Agents for Playing Splendor

Game-based benchmarks have been playing an essential role in the develop...

Ivan Bravi, et al. ∙

research

∙ 05/29/2019

A Topology Layer for Machine Learning

Topology applied to real world data using persistent homology has starte...

Rickard Brüel Gabrielsson, et al. ∙

research

∙ 08/07/2018

Universal Perceptual Grouping

In this work we aim to develop a universal sketch grouper. That is, a gr...

Ke Li, et al. ∙

research

∙ 04/28/2021

AMSS-Net: Audio Manipulation on User-Specified Sources with Textual Queries

This paper proposes a neural network that performs audio transformations...

Woosung Choi, et al. ∙

research

∙ 05/29/2022

Modeling Disagreement in Automatic Data Labelling for Semi-Supervised Learning in Clinical Natural Language Processing

Computational models providing accurate estimates of their uncertainty a...

Hongshu Liu, et al. ∙

research

∙ 05/14/2019

Generative Design in Minecraft: Chronicle Challenge

We introduce the Chronicle Challenge as an optional addition to the Sett...

Christoph Salge, et al. ∙

research

∙ 03/28/2022

A Framework of Meta Functional Learning for Regularising Knowledge Transfer

Machine learning classifiers' capability is largely dependent on the sca...

Pan Li, et al. ∙

research

∙ 07/13/2022

GriddlyJS: A Web IDE for Reinforcement Learning

Progress in reinforcement learning (RL) research is often driven by the ...

Christopher Bamford, et al. ∙

research

∙ 12/11/2018

Face-Focused Cross-Stream Network for Deception Detection in Videos

Automated deception detection (ADD) from real-life videos is a challengi...

Mingyu Ding, et al. ∙

research

∙ 07/22/2019

Universal Person Re-Identification

Most state-of-the-art person re-identification (re-id) methods depend on...

Xu Lan, et al. ∙

research

∙ 03/23/2020

Weighting NTBEA for Game AI Optimisation

The N-Tuple Bandit Evolutionary Algorithm (NTBEA) has proven very effect...

James Goodman, et al. ∙

research

∙ 10/11/2021

HUNTER: AI based Holistic Resource Management for Sustainable Cloud Computing

The worldwide adoption of cloud data centers (CDCs) has given rise to th...

Shreshth Tuli, et al. ∙

research

∙ 12/24/2021

Cluster-guided Image Synthesis with Unconditional Models

Generative Adversarial Networks (GANs) are the driving force behind the ...

Markos Georgopoulos, et al. ∙

research

∙ 06/10/2019

Project Thyia: A Forever Gameplayer

The space of Artificial Intelligence entities is dominated by conversati...

Raluca D. Gaina, et al. ∙

research

∙ 12/30/2019

Characteristic Regularisation for Super-Resolving Face Images

Existing facial image super-resolution (SR) methods focus mostly on impr...

Zhiyi Cheng, et al. ∙

research

∙ 05/28/2020

Boosting Few-Shot Learning With Adaptive Margin Loss

Few-shot learning (FSL) has attracted increasing attention in recent yea...

Aoxue Li, et al. ∙

research

∙ 10/28/2021

Dispensed Transformer Network for Unsupervised Domain Adaptation

Accurate segmentation is a crucial step in medical image analysis and ap...

Yunxiang Li, et al. ∙

research

∙ 02/14/2022

Permutation invariant matrix statistics and computational language tasks

The Linguistic Matrix Theory programme introduced by Kartsaklis, Ramgool...

Manuel Accettulli Huber, et al. ∙

research

∙ 05/13/2022

Multi-encoder Network for Parameter Reduction of a Kernel-based Interpolation Architecture

Video frame interpolation involves the synthesis of new frames from exis...

Issa Khalifeh, et al. ∙

research

∙ 06/25/2018

Person Re-Identification in Identity Regression Space

Most existing person re-identification (re-id) methods are unsuitable fo...

Hanxiao Wang, et al. ∙

research

∙ 10/29/2018

Concealing the identity of faces in oblique images with adaptive hopping Gaussian mixtures

Cameras mounted on Micro Aerial Vehicles (MAVs) are increasingly used fo...

Omair Sarwar, et al. ∙

research

∙ 03/01/2019

Unsupervised Tracklet Person Re-Identification

Most existing person re-identification (re-id) methods rely on supervise...

Minxian Li, et al. ∙

research

∙ 08/16/2019

Zero-Shot Crowd Behavior Recognition

Understanding crowd behavior in video is challenging for computer vision...

Xun Xu, et al. ∙

research

∙ 03/27/2020

Rolling Horizon Evolutionary Algorithms for General Video Game Playing

Game-playing Evolutionary Algorithms, specifically Rolling Horizon Evolu...

Raluca D. Gaina, et al. ∙

Queen Mary University of London

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