
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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SelfAssttentive Associative Memory
Heretofore, neural networks with external memory are restricted to singl...
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SelfAttentive Associative Memory
Heretofore, neural networks with external memory are restricted to singl...
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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 AIpowered agile project management
The rise of Artificial intelligence (AI) has the potential to significan...
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PIRM2018 Challenge on Spectral Image SuperResolution: 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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Superresolved Chromatic Mapping of Snapshot Mosaic Image Sensors via a Texture Sensitive Residual Network
This paper introduces a novel method to simultaneously superresolve 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 FineGrained Semantic Representations
Facial expression transfer between two unpaired images is a challenging ...
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A Visual Communication Map for MultiAgent Deep Reinforcement Learning
Multiagent learning distinctly poses significant challenges in the effo...
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Learning to Remember More with Less Memorization
Memoryaugmented neural networks consisting of a neural controller and a...
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KernelFree Image Deblurring with a Pair of Blurred/Noisy Images
Complex blur like the mixup of spacevariant and spaceinvariant 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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MultiAgent 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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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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MultiGenerator Generative Adversarial Nets
We propose a new approach to train the Generative Adversarial Nets (GANs...
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Analogicalbased Bayesian Optimization
Some realworld 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 pNorm 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 ngrams 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 1015 risk of infant mortali...
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An evaluation of randomized machine learning methods for redundant data: Predicting short and mediumterm 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 Largescale Online Learning
One of the most challenging problems in kernel online learning is to bou...
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Weakly monotone averaging functions
Monotonicity with respect to all arguments is fundamental to the definit...
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Treebased iterated local search for Markov random fields with applications in image analysis
The maximum a posteriori (MAP) assignment for general structure Markov r...
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Collaborative filtering via sparse Markov random fields
Recommender systems play a central role in providing individualized acce...
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A Robust 3D2D Interactive Tool for Scene Segmentation and Annotation
Recent advances of 3D acquisition devices have enabled largescale acqui...
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MultiResidual Networks: Improving the Speed and Accuracy of Residual Networks
In this article, we take one step toward understanding the learning beha...
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MixedVariate Restricted Boltzmann Machines
Modern datasets are becoming heterogeneous. To this end, we present in t...
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Thurstonian Boltzmann Machines: Learning from Multiple Inequalities
We introduce Thurstonian Boltzmann Machines (TBM), a unified architectur...
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Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis
Ordinal data is omnipresent in almost all multiusergenerated feedback ...
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Learning From Ordered Sets and Applications in Collaborative Ranking
Ranking over sets arise when users choose between groups of items. For e...
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A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network
We introduce a novel embedding method for knowledge base completion task...
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From Word Segmentation to POS Tagging for Vietnamese
This paper presents an empirical comparison of two strategies for Vietna...
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