
Learning Structral coherence Via Generative Adversarial Network for Single Image SuperResolution
Among the major remaining challenges for single image super resolution (...
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Generating a Doppelganger Graph: Resembling but Distinct
Deep generative models, since their inception, have become increasingly ...
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Directed Acyclic Graph Neural Networks
Graphstructured data ubiquitously appears in science and engineering. G...
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Discrete Graph Structure Learning for Forecasting Multiple Time Series
Time series forecasting is an extensively studied subject in statistics,...
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Handling Noisy Labels via OneStep Abductive MultiTarget Learning
Learning from noisy labels is an important concern because of the lack o...
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Edge Adaptive Hybrid Regularization Model For Image Deblurring
A spatially fixed parameter of regularization item for whole images does...
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A Bounded MultiVacation Queue Model for Multistage Sleep Control 5G Base station
Modelling and control of energy consumption is an important problem in t...
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Deep reinforcement learning for RAN optimization and control
Due to the high variability of the traffic in the radio access network (...
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Hyperspectral Unmixing via Nonnegative Matrix Factorization with Handcrafted and Learnt Priors
Nowadays, nonnegative matrix factorization (NMF) based methods have been...
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Deep Selective Combinatorial Embedding and Consistency Regularization for Light Field Superresolution
Light field (LF) images acquired by handheld devices usually suffer fro...
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The 1st Tiny Object Detection Challenge:Methods and Results
The 1st Tiny Object Detection (TOD) Challenge aims toencourage research ...
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Distributed Linear Equations over Random Networks
Distributed linear algebraic equation over networks, where nodes hold a ...
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Surrogate LocallyInterpretable Models with Supervised Machine Learning Algorithms
Supervised Machine Learning (SML) algorithms, such as Gradient Boosting,...
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Deep Learning Methods for Solving Linear Inverse Problems: Research Directions and Paradigms
The linear inverse problem is fundamental to the development of various ...
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Generalized multiscale approximation of a multipoint flux mixed finite element method for DarcyForchheimer model
In this paper, we propose a multiscale method for the DarcyForchheimer ...
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Adaptive generalized multiscale approximation of a mixed finite element method with velocity elimination
In this paper, we propose offline and online adaptive enrichment algorit...
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Hyperspectral Image Superresolution via Deep Progressive Zerocentric Residual Learning
This paper explores the problem of hyperspectral image (HSI) superresol...
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Policy Gradient from Demonstration and Curiosity
With reinforcement learning, an agent could learn complex behaviors from...
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ADCluster: Augmented Discriminative Clustering for Domain Adaptive Person Reidentification
Domain adaptive person reidentification (reID) is a challenging task, ...
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Adaptive Explainable Neural Networks (AxNNs)
While machine learning techniques have been successfully applied in seve...
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Light Field Spatial Superresolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization
Light field (LF) images acquired by handheld devices usually suffer fro...
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Learning a WeaklySupervised Video ActorAction Segmentation Model with a Wise Selection
We address weaklysupervised video actoraction segmentation (VAAS), whi...
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Automated discovery of a robust interatomic potential for aluminum
Atomistic molecular dynamics simulation is an important tool for predict...
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DASNet: Dual attentive fully convolutional siamese networks for change detection of high resolution satellite images
Change detection is a basic task of remote sensing image processing. The...
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Asynchronous parallel adaptive stochastic gradient methods
Stochastic gradient methods (SGMs) are the predominant approaches to tra...
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Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models
Deep neural networks, while generalize well, are known to be sensitive t...
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Linearly Convergent Algorithm with Variance Reduction for Distributed Stochastic Optimization
This paper considers a distributed stochastic strongly convex optimizati...
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Convolution Neural Network Architecture Learning for Remote Sensing Scene Classification
Remote sensing image scene classification is a fundamental but challengi...
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Embedding Compression with Isotropic Iterative Quantization
Continuous representation of words is a standard component in deep learn...
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Multitask learning over graphs
The problem of learning simultaneously several related tasks has receive...
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Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
Hierarchical abstractions are a methodology for solving largescale grap...
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Chart AutoEncoders for Manifold Structured Data
Autoencoding and generative models have made tremendous successes in im...
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A multilabel classification method using a hierarchical and transparent representation for paperreviewer recommendation
Paperreviewer recommendation task is of significant academic importance...
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CAG: A Realtime Lowcost Enhancedrobustness Hightransferability Contentaware Adversarial Attack Generator
Deep neural networks (DNNs) are vulnerable to adversarial attack despite...
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Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression
This paper presents a variational Bayesian kernel selection (VBKS) algor...
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DFSMNSAN with Persistent Memory Model for Automatic Speech Recognition
Selfattention networks (SAN) have been introduced into automatic speech...
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Adaptively Aligned Image Captioning via Adaptive Attention Time
Recent neural models for image captioning usually employs an encoderdec...
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Flexible, Fast and Accurate DenselySampled Light Field Reconstruction Network
The denselysampled light field (LF) is highly desirable in various appl...
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Attention on Attention for Image Captioning
Attention mechanisms are widely used in current encoder/decoder framewor...
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AntiMoney Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
Antimoney laundering (AML) regulations play a critical role in safeguar...
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Learning Highfidelity Light Field Images From Hybrid Inputs
This paper explores the reconstruction of highfidelity LF images (i.e.,...
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Distributed Global OutputFeedback Control for a Class of EulerLagrange Systems
This published paper investigates the distributed tracking control probl...
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Large Intelligent Surface/Antennas (LISA): Making Reflective Radios Smart
Large intelligent surface/antennas (LISA), a twodimensional artificial ...
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Learning discriminative features in sequence training without requiring framewise labelled data
In this work, we try to answer two questions: Can deeply learned feature...
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IPC: A Benchmark Data Set for Learning with GraphStructured Data
Benchmark data sets are an indispensable ingredient of the evaluation of...
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Time Series Simulation by Conditional Generative Adversarial Net
Generative Adversarial Net (GAN) has been proven to be a powerful machin...
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DAGGNN: DAG Structure Learning with Graph Neural Networks
Learning a faithful directed acyclic graph (DAG) from samples of a joint...
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A Data Driven Approach for Motion Planning of Autonomous Driving Under Complex Scenario
To guarantee the safe and efficient motion planning of autonomous drivin...
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A Sequential Set Generation Method for Predicting SetValued Outputs
Consider a general machine learning setting where the output is a set of...
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Stratified Labeling for Surface Consistent Parallax Correction and Occlusion Completion
The light field faithfully records the spatial and angular configuration...
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Jie Chen
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City University of Hong Kong
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MIT
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ibm
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University of Oulu
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Alibaba Cloud
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Université Nice Sophia Antipolis
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IEEE
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Hong Kong Baptist University
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Institute of Computing Technology, Chinese Academy of Sciences
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Nanyang Technological University
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University of Rochester
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Tencent
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Shenzhen University
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Peking University
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Durham University
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Beijing Institute of Technology
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NetEase, Inc
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