The University of Manchester

research

∙ 10/29/2021

MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare

Mental health is a critical issue in modern society, and mental disorder...

Shaoxiong Ji, et al. ∙

research

∙ 01/28/2020

Margin Maximization as Lossless Maximal Compression

The ultimate goal of a supervised learning algorithm is to produce model...

Nikolaos Nikolaou, et al. ∙

research

∙ 02/28/2021

Exploring the social influence of Kaggle virtual community on the M5 competition

One of the most significant differences of M5 over previous forecasting ...

Xixi Li, et al. ∙

research

∙ 08/01/2021

Realised Volatility Forecasting: Machine Learning via Financial Word Embedding

We develop FinText, a novel, state-of-the-art, financial word embedding ...

Eghbal Rahimikia, et al. ∙

research

∙ 09/19/2021

Ontology-based n-ball Concept Embeddings Informing Few-shot Image Classification

We propose a novel framework named ViOCE that integrates ontology-based ...

Mirantha Jayathilaka, et al. ∙

research

∙ 02/03/2022

HRBF-Fusion: Accurate 3D reconstruction from RGB-D data using on-the-fly implicits

Reconstruction of high-fidelity 3D objects or scenes is a fundamental re...

Yabin Xu, et al. ∙

research

∙ 03/01/2022

Distributional Reinforcement Learning for Scheduling of (Bio)chemical Production Processes

Reinforcement Learning (RL) has recently received significant attention ...

Max Mowbray, et al. ∙

research

∙ 01/16/2020

Better Boosting with Bandits for Online Learning

Probability estimates generated by boosting ensembles are poorly calibra...

Nikolaos Nikolaou, et al. ∙

research

∙ 07/09/2019

A Deep Neural Network for Finger Counting and Numerosity Estimation

In this paper, we present neuro-robotics models with a deep artificial n...

Leszek Pecyna, et al. ∙

research

∙ 08/30/2019

Multi-Temporal High Resolution Aerial Image Registration Using Semantic Features

A new type of segmentation-based semantic feature (SegSF) for multi-temp...

Ananya Gupta, et al. ∙

research

∙ 05/18/2021

Learning and Information in Stochastic Networks and Queues

We review the role of information and learning in the stability and opti...

Neil Walton, 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

∙ 12/03/2019

ATIS + SpiNNaker: a Fully Event-based Visual Tracking Demonstration

The Asynchronous Time-based Image Sensor (ATIS) and the Spiking Neural N...

Arren Glover, et al. ∙

research

∙ 07/25/2021

Hybrid Autoregressive Solver for Scalable Abductive Natural Language Inference

Regenerating natural language explanations for science questions is a ch...

Marco Valentino, et al. ∙

research

∙ 09/15/2017

Multi-Label Zero-Shot Human Action Recognition via Joint Latent Embedding

Human action recognition refers to automatic recognizing human actions f...

Qian Wang, et al. ∙

research

∙ 09/12/2017

Meta-QSAR: a large-scale application of meta-learning to drug design and discovery

We investigate the learning of quantitative structure activity relations...

Ivan Olier, et al. ∙

research

∙ 08/30/2016

Visualisation of Survey Responses using Self-Organising Maps: A Case Study on Diabetes Self-care Factors

Due to the chronic nature of diabetes, patient self-care factors play an...

Santosh Tirunagari, et al. ∙

research

∙ 07/13/2017

Dependency Injection for Programming by Optimization

Programming by Optimization tools perform automatic software configurati...

Zoltan A. Kocsis, et al. ∙

research

∙ 04/02/2017

Identifying networks with common organizational principles

Many complex systems can be represented as networks, and the problem of ...

Anatol E. Wegner, et al. ∙

research

∙ 06/28/2017

Alternative Semantic Representations for Zero-Shot Human Action Recognition

A proper semantic representation for encoding side information is key to...

Qian Wang, et al. ∙

research

∙ 09/04/2012

Monotonicity of Fitness Landscapes and Mutation Rate Control

The typical view in evolutionary biology is that mutation rates are mini...

Roman V. Belavkin, et al. ∙

research

∙ 08/04/2016

Deploying learning materials to game content for serious education game development: A case study

The ultimate goals of serious education games (SEG) are to facilitate le...

Harits Ar Rosyid, et al. ∙

research

∙ 11/05/2006

An associative memory for the on-line recognition and prediction of temporal sequences

This paper presents the design of an associative memory with feedback th...

J. Bose, et al. ∙

research

∙ 10/27/2016

GPflow: A Gaussian process library using TensorFlow

GPflow is a Gaussian process library that uses TensorFlow for its core c...

Alexander G. de G. Matthews, et al. ∙

research

∙ 06/02/2000

Novelty Detection on a Mobile Robot Using Habituation

In this paper a novelty filter is introduced which allows a robot operat...

Stephen Marsland, et al. ∙

research

∙ 06/02/2000

A Real-Time Novelty Detector for a Mobile Robot

Recognising new or unusual features of an environment is an ability whic...

Stephen Marsland, et al. ∙

research

∙ 06/02/2000

Novelty Detection for Robot Neotaxis

The ability of a robot to detect and respond to changes in its environme...

Stephen Marsland, et al. ∙

research

∙ 10/27/2015

Learning Constructive Primitives for Online Level Generation and Real-time Content Adaptation in Super Mario Bros

Procedural content generation (PCG) is of great interest to game design ...

Peizhi Shi, et al. ∙

research

∙ 04/14/2015

Temporal ordering of clinical events

This report describes a minimalistic set of methods engineered to anchor...

Azad Dehghan, et al. ∙

research

∙ 05/16/2014

Algorithm for Adapting Cases Represented in a Tractable Description Logic

Case-based reasoning (CBR) based on description logics (DLs) has gained ...

Liang Chang, et al. ∙

research

∙ 07/07/2016

Zero-Shot Visual Recognition via Bidirectional Latent Embedding

Zero-shot learning for visual recognition, e.g., object and action recog...

Qian Wang, et al. ∙

research

∙ 07/06/2012

Syntactic vs. Semantic Locality: How Good Is a Cheap Approximation?

Extracting a subset of a given OWL ontology that captures all the ontolo...

Chiara Del Vescovo, et al. ∙

research

∙ 11/11/2015

Principal Autoparallel Analysis: Data Analysis in Weitzenböck Space

The statistical analysis of data lying on a differentiable, locally Eucl...

Stephen Marsland, et al. ∙

research

∙ 10/31/2011

Reasoning with Very Expressive Fuzzy Description Logics

It is widely recognized today that the management of imprecision and vag...

I. Horrocks, et al. ∙

research

∙ 07/25/2011

Variational Gaussian Process Dynamical Systems

High dimensional time series are endemic in applications of machine lear...

Andreas C. Damianou, et al. ∙

research

∙ 09/15/2015

Direct high-order edge-preserving regularization for tomographic image reconstruction

In this paper we present a new two-level iterative algorithm for tomogra...

Daniil Kazantsev, et al. ∙

research

∙ 06/01/2015

Robust Face Recognition with Structural Binary Gradient Patterns

This paper presents a computationally efficient yet powerful binary fram...

Weilin Huang, et al. ∙

research

∙ 01/15/2013

Multi-agent learning using Fictitious Play and Extended Kalman Filter

Decentralised optimisation tasks are important components of multi-agent...

Michalis Smyrnakis, et al. ∙

research

∙ 05/19/2009

A Note on the Complexity of the Satisfiability Problem for Graded Modal Logics

Graded modal logic is the formal language obtained from ordinary (propos...

Yevgeny Kazakov, et al. ∙

research

∙ 09/26/2012

Bayesian Mixture Models for Frequent Itemset Discovery

In binary-transaction data-mining, traditional frequent itemset mining o...

Ruefei He, et al. ∙

research

∙ 12/11/2011

Adaptive Forgetting Factor Fictitious Play

It is now well known that decentralised optimisation can be formulated a...

Michalis Smyrnakis, et al. ∙

research

∙ 05/11/2000

Reasoning with Individuals for the Description Logic SHIQ

While there has been a great deal of work on the development of reasonin...

Ian Horrock, et al. ∙

research

∙ 05/10/2000

Practical Reasoning for Expressive Description Logics

Description Logics (DLs) are a family of knowledge representation formal...

Ian Horrocks, et al. ∙

research

∙ 05/09/2000

Practical Reasoning for Very Expressive Description Logics

Description Logics (DLs) are a family of knowledge representation formal...

Ian Horrocks, et al. ∙

research

∙ 05/09/2000

Reasoning with Axioms: Theory and Pratice

When reasoning in description, modal or temporal logics it is often usef...

Ian Horrocks, et al. ∙

research

∙ 12/16/2009

Variational Inducing Kernels for Sparse Convolved Multiple Output Gaussian Processes

Interest in multioutput kernel methods is increasing, whether under the ...

Mauricio A. Álvarez, et al. ∙

research

∙ 11/26/2009

Sparse Convolved Multiple Output Gaussian Processes

Recently there has been an increasing interest in methods that deal with...

Mauricio A. Álvarez, et al. ∙

research

∙ 10/22/2017

How big is big enough? Unsupervised word sense disambiguation using a very large corpus

In this paper, the problem of disambiguating a target word for Polish is...

Piotr Przybyła, et al. ∙

research

∙ 09/03/2017

Investigating how well contextual features are captured by bi-directional recurrent neural network models

Learning algorithms for natural language processing (NLP) tasks traditio...

Kushal Chawla, et al. ∙

research

∙ 03/14/2017

A computational investigation of sources of variability in sentence comprehension difficulty in aphasia

We present a computational evaluation of three hypotheses about sources ...

Paul Mätzig, et al. ∙

The University of Manchester

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