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Multi-Modal Domain Adaptation for Fine-Grained Action Recognition
Fine-grained action recognition datasets exhibit environmental bias, whe...
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One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency
The need for transparency of predictive systems based on Machine Learnin...
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FAT Forensics: A Python Toolbox for Algorithmic Fairness, Accountability and Transparency
Machine learning algorithms can take important decisions, sometimes lega...
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Prediction of Thrombectomy FunctionalOutcomes using Multimodal Data
Recent randomised clinical trials have shown that patients with ischaemi...
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Video compression with low complexity CNN-based spatial resolution adaptation
It has recently been demonstrated that spatial resolution adaptation can...
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Are there any 'object detectors' in the hidden layers of CNNs trained to identify objects or scenes?
Various methods of measuring unit selectivity have been developed with t...
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Supervision Levels Scale (SLS)
We propose a three-dimensional discrete and incremental scale to encode ...
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Visual Identification of Individual Holstein Friesian Cattle via Deep Metric Learning
Holstein Friesian cattle exhibit individually-characteristic black and w...
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Retro-Actions: Learning 'Close' by Time-Reversing 'Open' Videos
We investigate video transforms that result in class-homogeneous label-t...
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TripleTree: A Versatile Interpretable Representation of Black Box Agents and their Environments
In explainable artificial intelligence, there is increasing interest in ...
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FACE: Feasible and Actionable Counterfactual Explanations
Work in Counterfactual Explanations tends to focus on the principle of "...
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Modelling Agent Policies with Interpretable Imitation Learning
As we deploy autonomous agents in safety-critical domains, it becomes im...
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HyperStream: a Workflow Engine for Streaming Data
This paper describes HyperStream, a large-scale, flexible and robust sof...
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Registration-free Face-SSD: Single shot analysis of smiles, facial attributes, and affect in the wild
In this paper, we present a novel single shot face-related task analysis...
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Prediction of Thrombectomy Functional Outcomes using Multimodal Data
Recent randomised clinical trials have shown that patients with ischaemi...
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N2D:(Not Too) Deep clustering via clustering the local manifold of an autoencoded embedding
Deep clustering has increasingly been demonstrating superiority over con...
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Right for the Right Reason: Training Agnostic Networks
We consider the problem of a neural network being requested to classify ...
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Non-Parametric Calibration of Probabilistic Regression
The task of calibration is to retrospectively adjust the outputs from a ...
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On the Learnability of Concepts: With Applications to Comparing Word Embedding Algorithms
Word Embeddings are used widely in multiple Natural Language Processing ...
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Road surface 3d reconstruction based on dense subpixel disparity map estimation
Various 3D reconstruction methods have enabled civil engineers to detect...
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Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance
In recent years there has been a growing interest in image generation th...
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Bayesian nonparametric shared multi-sequence time series segmentation
In this paper, we introduce a method for segmenting time series data usi...
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CaloriNet: From silhouettes to calorie estimation in private environments
We propose a novel deep fusion architecture, CaloriNet, for the online e...
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BVI-DVC: A Training Database for Deep Video Compression
Deep learning methods are increasingly being applied in the optimisation...
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Deep Learning Framework for Detecting Ground Deformation in the Built Environment using Satellite InSAR data
The large volumes of Sentinel-1 data produced over Europe are being used...
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LIMEtree: Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees
Systems based on artificial intelligence and machine learning models sho...
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Beyond No Free Lunch: Realistic Algorithms for Arbitrary Problem Classes
We show how the necessary and sufficient conditions for the NFL to apply...
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Reliability of Broadcast Communications Under Sparse Random Linear Network Coding
Ultra-reliable Point-to-Multipoint (PtM) communications are expected to ...
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Neural Translation of Musical Style
Music is an expressive form of communication often used to convey emotio...
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Detecting the Moment of Completion: Temporal Models for Localising Action Completion
Action completion detection is the problem of modelling the action's pro...
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Asymptotic Bias of Stochastic Gradient Search
The asymptotic behavior of the stochastic gradient algorithm with a bias...
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Towards CNN map representation and compression for camera relocalisation
This paper presents a study on the use of Convolutional Neural Networks ...
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Latent Gaussian Process Regression
We introduce Latent Gaussian Process Regression which is a latent variab...
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A Model of Multi-Agent Consensus for Vague and Uncertain Beliefs
Consensus formation is investigated for multi-agent systems in which age...
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Trimmed Density Ratio Estimation
Density ratio estimation is a vital tool in both machine learning and st...
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Model-based Test Generation for Robotic Software: Automata versus Belief-Desire-Intention Agents
Robotic code needs to be verified to ensure its safety and functional co...
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Exploiting Vagueness for Multi-Agent Consensus
A framework for consensus modelling is introduced using Kleene's three v...
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Probabilistic Sensor Fusion for Ambient Assisted Living
There is a widely-accepted need to revise current forms of health-care p...
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A KdV-like advection-dispersion equation with some remarkable properties
We discuss a new non-linear PDE, u_t + (2 u_xx/u) u_x = epsilon u_xxx, i...
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Manifold Alignment Determination: finding correspondences across different data views
We present Manifold Alignment Determination (MAD), an algorithm for lear...
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Geometric Affordances from a Single Example via the Interaction Tensor
This paper develops and evaluates a new tensor field representation to e...
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Emerging Dimension Weights in a Conceptual Spaces Model of Concept Combination
We investigate the generation of new concepts from combinations of prope...
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The Utility of Hedged Assertions in the Emergence of Shared Categorical Labels
We investigate the emergence of shared concepts in a community of langua...
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A Label Semantics Approach to Linguistic Hedges
We introduce a model for the linguistic hedges `very' and `quite' within...
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Concept Generation in Language Evolution
This thesis investigates the generation of new concepts from combination...
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Towards CNN Map Compression for camera relocalisation
This paper presents a study on the use of Convolutional Neural Networks ...
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Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model
Unsupervised learning on imbalanced data is challenging because, when gi...
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Detecting People in Artwork with CNNs
CNNs have massively improved performance in object detection in photogra...
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On the Geometric Ergodicity of Hamiltonian Monte Carlo
We establish general conditions under which Markov chains produced by th...
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Automated Visual Fin Identification of Individual Great White Sharks
This paper discusses the automated visual identification of individual g...
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