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InceptionTime: Finding AlexNet for Time Series Classification
Time series classification (TSC) is the area of machine learning interes...
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A Bayesian-inspired, deep learning, semi-supervised domain adaptation technique for land cover mapping
Land cover maps are a vital input variable to many types of environmenta...
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Low radiation tomographic reconstruction with and without template information
Low-dose tomography is highly preferred in medical procedures for its re...
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Hierarchical forecast reconciliation with machine learning
Hierarchical forecasting methods have been widely used to support aligne...
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Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions
Deep neural network image classifiers are reported to be susceptible to ...
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Blockwisely Supervised Neural Architecture Search with Knowledge Distillation
Neural Architecture Search (NAS), aiming at automatically designing netw...
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Speak2Label: Using Domain Knowledge for Creating a Large Scale Driver Gaze Zone Estimation Dataset
Labelling of human behavior analysis data is a complex and time consumin...
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Active Preference Learning using Maximum Regret
We study active preference learning as a framework for intuitively speci...
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LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series with Multiple Seasonal Patterns
Generating forecasts for time series with multiple seasonal cycles is an...
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Generating Semantic Adversarial Examples via Feature Manipulation
The vulnerability of deep neural networks to adversarial attacks has bee...
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Learning Coupled Policies for Simultaneous Machine Translation
In simultaneous machine translation, the system needs to incrementally g...
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A Survey on Knowledge Graphs: Representation, Acquisition and Applications
Human knowledge provides a formal understanding of the world. Knowledge ...
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OIAD: One-for-all Image Anomaly Detection with Disentanglement Learning
Anomaly detection aims to recognize samples with anomalous and unusual p...
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ZSTAD: Zero-Shot Temporal Activity Detection
An integral part of video analysis and surveillance is temporal activity...
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Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks
Influence maximization is a widely studied topic in network science, whe...
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Not made for each other- Audio-Visual Dissonance-based Deepfake Detection and Localization
We propose detection of deepfake videos based on the dissimilarity betwe...
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OpenGAN: Open Set Generative Adversarial Networks
Many existing conditional Generative Adversarial Networks (cGANs) are li...
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Understanding Aesthetic Evaluation using Deep Learning
A bottleneck in any evolutionary art system is aesthetic evaluation. Man...
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Towards effective AI-powered agile project management
The rise of Artificial intelligence (AI) has the potential to significan...
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Auxiliary Signal-Guided Knowledge Encoder-Decoder for Medical Report Generation
Beyond the common difficulties faced in the natural image captioning, me...
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LoRMIkA: Local Rule-based Model Interpretability with k-optimal Associations
As we rely more and more on machine learning models for real-life decisi...
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Real-time Fruit Recognition and Grasp Estimation for Autonomous Apple harvesting
In this research, a fully neural network based visual perception framewo...
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Improving Adversarial Robustness by Enforcing Local and Global Compactness
The fact that deep neural networks are susceptible to crafted perturbati...
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DeepPayload: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection
Deep learning models are increasingly used in mobile applications as cri...
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ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs
Recovering structure and motion parameters given a image pair or a seque...
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Searching with Consistent Prioritization for Multi-Agent Path Finding
We study prioritized planning for Multi-Agent Path Finding (MAPF). Exist...
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Adversarial Graph Embeddings for Fair Influence Maximization over SocialNetworks
Influence maximization is a widely studied topic in network science, whe...
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Seasonal Averaged One-Dependence Estimators: A Novel Algorithm to Address Seasonal Concept Drift in High-Dimensional Stream Classification
Stream classification methods classify a continuous stream of data as ne...
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Expert Training: Task Hardness Aware Meta-Learning for Few-Shot Classification
Deep neural networks are highly effective when a large number of labeled...
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Faster and More Robust Mesh-based Algorithms for Obstacle k-Nearest Neighbour
We are interested in the problem of finding k nearest neighbours in the ...
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Position Paper: From Multi-Agent Pathfinding to Pipe Routing
The 2D Multi-Agent Path Finding (MAPF) problem aims at finding collision...
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Bridge the Domain Gap Between Ultra-wide-field and Traditional Fundus Images via Adversarial Domain Adaptation
For decades, advances in retinal imaging technology have enabled effecti...
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Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness
It has been demonstrated that hidden representation learned by a deep mo...
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Robustness Evaluation of Stacked Generative Adversarial Networks using Metamorphic Testing
Synthesising photo-realistic images from natural language is one of the ...
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Traversing Latent Space using Decision Ferns
The practice of transforming raw data to a feature space so that inferen...
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EMPNet: Neural Localisation and Mapping using Embedded Memory Points
Continuously estimating an agent's state space and a representation of i...
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Exploring Bottom-up and Top-down Cues with Attentive Learning for Webly Supervised Object Detection
Fully supervised object detection has achieved great success in recent y...
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Losing Confidence in Quality: Unspoken Evolution of Computer Vision Services
Recent advances in artificial intelligence (AI) and machine learning (ML...
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A novel activity pattern generation incorporating deep learning for transport demand models
Activity generation plays an important role in activity-based demand mod...
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Predicting proximity with ambient mobile sensors for non-invasive health diagnostics
Modern smart phones are becoming helpful in the areas of Internet-Of-Thi...
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Tomographic Reconstruction using Global Statistical Prior
Recent research in tomographic reconstruction is motivated by the need t...
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Specious rules: an efficient and effective unifying method for removing misleading and uninformative patterns in association rule mining
We present theoretical analysis and a suite of tests and procedures for ...
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Word Representation Models for Morphologically Rich Languages in Neural Machine Translation
Dealing with the complex word forms in morphologically rich languages is...
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Accurate parameter estimation for Bayesian Network Classifiers using Hierarchical Dirichlet Processes
This paper introduces a novel parameter estimation method for the probab...
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RKL: a general, invariant Bayes solution for Neyman-Scott
Neyman-Scott is a classic example of an estimation problem with a partia...
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Towards Decoding as Continuous Optimization in Neural Machine Translation
We propose a novel decoding approach for neural machine translation (NMT...
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A Fast Method For Computing Principal Curvatures From Range Images
Estimation of surface curvature from range data is important for a range...
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Joint Pose and Principal Curvature Refinement Using Quadrics
In this paper we present a novel joint approach for optimising surface c...
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Nearest Neighbour Radial Basis Function Solvers for Deep Neural Networks
We present a radial basis function solver for convolutional neural netwo...
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Latent Variable Discovery Using Dependency Patterns
The causal discovery of Bayesian networks is an active and important res...
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