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Improving Generalization and Stability of Generative Adversarial Networks
Generative Adversarial Networks (GANs) are one of the most popular tools...
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Review, Analyze, and Design a Comprehensive Deep Reinforcement Learning Framework
Reinforcement learning (RL) has emerged as a standard approach for build...
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Distributionally Robust Bayesian Quadrature Optimization
Bayesian quadrature optimization (BQO) maximizes the expectation of an e...
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Spoof Face Detection Via Semi-Supervised Adversarial Training
Face spoofing causes severe security threats in face recognition systems...
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What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space
Deep neural networks (DNNs) have been widely adopted in different applic...
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Self-Assttentive Associative Memory
Heretofore, neural networks with external memory are restricted to singl...
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Self-Attentive Associative Memory
Heretofore, neural networks with external memory are restricted to singl...
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Hierarchical Conditional Relation Networks for Multimodal Video Question Answering
Video QA challenges modelers in multiple fronts. Modeling video necessit...
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Interpretable and Efficient Heterogeneous Graph Convolutional Network
Graph Convolutional Network (GCN) has achieved extraordinary success in ...
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SSIMLayer: Towards Robust Deep Representation Learning via Nonlinear Structural Similarity
Deeper convolutional neural networks provide more capacity to approximat...
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Bayesian functional optimisation with shape prior
Real world experiments are expensive, and thus it is important to reach ...
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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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PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study
This paper introduces a newly collected and novel dataset (StereoMSI) fo...
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Theory and Evaluation Metrics for Learning Disentangled Representations
We make two theoretical contributions to disentanglement learning by (a)...
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Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks
Recent studies have shown that DNNs can be compromised by backdoor attac...
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Super-resolved Chromatic Mapping of Snapshot Mosaic Image Sensors via a Texture Sensitive Residual Network
This paper introduces a novel method to simultaneously super-resolve and...
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Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos
Appearance features have been widely used in video anomaly detection eve...
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Explicit Facial Expression Transfer via Fine-Grained Semantic Representations
Facial expression transfer between two unpaired images is a challenging ...
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A Visual Communication Map for Multi-Agent Deep Reinforcement Learning
Multi-agent learning distinctly poses significant challenges in the effo...
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Learning to Remember More with Less Memorization
Memory-augmented neural networks consisting of a neural controller and a...
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Kernel-Free Image Deblurring with a Pair of Blurred/Noisy Images
Complex blur like the mixup of space-variant and space-invariant blur, w...
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Learning to Reason with Relational Video Representation for Question Answering
How does machine learn to reason about the content of a video in answeri...
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Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling
Scientific experiments are usually expensive due to complex experimental...
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Incorporating Expert Prior in Bayesian Optimisation via Space Warping
Bayesian optimisation is a well-known sample-efficient method for the op...
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An Uncertainty-aware Transfer Learning-based Framework for Covid-19 Diagnosis
The early and reliable detection of COVID-19 infected patients is essent...
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Multi-Agent Deep Reinforcement Learning with Human Strategies
Deep learning has enabled traditional reinforcement learning methods to ...
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On catastrophic forgetting and mode collapse in Generative Adversarial Networks
Generative Adversarial Networks (GAN) are one of the most prominent tool...
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Warwick Image Forensics Dataset for Device Fingerprinting In Multimedia Forensics
Device fingerprints like sensor pattern noise (SPN) are widely used for ...
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Age-Oriented Face Synthesis with Conditional Discriminator Pool and Adversarial Triplet Loss
The vanilla Generative Adversarial Networks (GAN) are commonly used to g...
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HDF: Hybrid Deep Features for Scene Image Representation
Nowadays it is prevalent to take features extracted from pre-trained dee...
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Imbalanced Gradients: A New Cause of Overestimated Adversarial Robustness
Evaluating the robustness of a defense model is a challenging task in ad...
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Automatic feature learning for vulnerability prediction
Code flaws or vulnerabilities are prevalent in software systems and can ...
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KGAN: How to Break The Minimax Game in GAN
Generative Adversarial Networks (GANs) were intuitively and attractively...
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Creating a Social Brain for Cooperative Connected Autonomous Vehicles: Issues and Challenges
The connected autonomous vehicle has been often touted as a technology t...
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Geometric Enclosing Networks
Training model to generate data has increasingly attracted research atte...
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Multi-Generator Generative Adversarial Nets
We propose a new approach to train the Generative Adversarial Nets (GANs...
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Analogical-based Bayesian Optimization
Some real-world problems revolve to solve the optimization problem _x∈Xf...
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Dual Discriminator Generative Adversarial Nets
We propose in this paper a novel approach to tackle the problem of mode ...
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Faster Training of Very Deep Networks Via p-Norm Gates
A major contributing factor to the recent advances in deep neural networ...
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Statistical Latent Space Approach for Mixed Data Modelling and Applications
The analysis of mixed data has been raising challenges in statistics and...
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Wind ramp event prediction with parallelized Gradient Boosted Regression Trees
Accurate prediction of wind ramp events is critical for ensuring the rel...
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A Random Finite Set Model for Data Clustering
The goal of data clustering is to partition data points into groups to m...
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Robust artificial neural networks and outlier detection. Technical report
Large outliers break down linear and nonlinear regression models. Robust...
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Stabilizing Linear Prediction Models using Autoencoder
To date, the instability of prognostic predictors in a sparse high dimen...
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A deep learning model for estimating story points
Although there has been substantial research in software analytics for e...
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A deep language model for software code
Existing language models such as n-grams for software code often fail to...
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DeepSoft: A vision for a deep model of software
Although software analytics has experienced rapid growth as a research a...
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Preterm Birth Prediction: Deriving Stable and Interpretable Rules from High Dimensional Data
Preterm births occur at an alarming rate of 10-15 risk of infant mortali...
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An evaluation of randomized machine learning methods for redundant data: Predicting short and medium-term suicide risk from administrative records and risk assessments
Accurate prediction of suicide risk in mental health patients remains an...
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Approximation Vector Machines for Large-scale Online Learning
One of the most challenging problems in kernel online learning is to bou...
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