Jie Chen

Handling Noisy Labels via One-Step Abductive Multi-Target Learning

Learning from noisy labels is an important concern because of the lack o...
11/25/2020 ∙ by Yongquan Yang, et al. ∙ 9 ∙ share

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Edge Adaptive Hybrid Regularization Model For Image Deblurring

A spatially fixed parameter of regularization item for whole images does...
11/20/2020 ∙ by Jie Chen, et al. ∙ 2 ∙ share

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A Bounded Multi-Vacation Queue Model for Multi-stage Sleep Control 5G Base station

Modelling and control of energy consumption is an important problem in t...
11/19/2020 ∙ by Jie Chen, et al. ∙ 0 ∙ share

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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 (...
11/09/2020 ∙ by Yu Chen, et al. ∙ 21 ∙ share

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Hyperspectral Unmixing via Nonnegative Matrix Factorization with Handcrafted and Learnt Priors

Nowadays, nonnegative matrix factorization (NMF) based methods have been...
10/09/2020 ∙ by Min Zhao, et al. ∙ 15 ∙ share

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Deep Selective Combinatorial Embedding and Consistency Regularization for Light Field Super-resolution

Light field (LF) images acquired by hand-held devices usually suffer fro...
09/26/2020 ∙ by Jing Jin, et al. ∙ 3 ∙ share

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The 1st Tiny Object Detection Challenge:Methods and Results

The 1st Tiny Object Detection (TOD) Challenge aims toencourage research ...
09/16/2020 ∙ by Xuehui Yu, et al. ∙ 16 ∙ share

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Distributed Linear Equations over Random Networks

Distributed linear algebraic equation over networks, where nodes hold a ...
08/22/2020 ∙ by Peng Yi, et al. ∙ 0 ∙ share

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Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms

Supervised Machine Learning (SML) algorithms, such as Gradient Boosting,...
07/28/2020 ∙ by Linwei Hu, et al. ∙ 27 ∙ share

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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 ...
07/27/2020 ∙ by Yanna Bai, et al. ∙ 0 ∙ share

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Generalized multiscale approximation of a multipoint flux mixed finite element method for Darcy-Forchheimer model

In this paper, we propose a multiscale method for the Darcy-Forchheimer ...
07/17/2020 ∙ by Zhengkang He, et al. ∙ 0 ∙ share

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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...
07/17/2020 ∙ by Zhengkang He, et al. ∙ 0 ∙ share

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Hyperspectral Image Super-resolution via Deep Progressive Zero-centric Residual Learning

This paper explores the problem of hyperspectral image (HSI) super-resol...
06/18/2020 ∙ by Zhiyu Zhu, et al. ∙ 0 ∙ share

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Policy Gradient from Demonstration and Curiosity

With reinforcement learning, an agent could learn complex behaviors from...
04/22/2020 ∙ by Jie Chen, et al. ∙ 19 ∙ share

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AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification

Domain adaptive person re-identification (re-ID) is a challenging task, ...
04/19/2020 ∙ by Yunpeng Zhai, et al. ∙ 0 ∙ share

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Adaptive Explainable Neural Networks (AxNNs)

While machine learning techniques have been successfully applied in seve...
04/05/2020 ∙ by Jie Chen, et al. ∙ 108 ∙ share

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Light Field Spatial Super-resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization

Light field (LF) images acquired by hand-held devices usually suffer fro...
04/05/2020 ∙ by Jing Jin, et al. ∙ 1 ∙ share

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Learning a Weakly-Supervised Video Actor-Action Segmentation Model with a Wise Selection

We address weakly-supervised video actor-action segmentation (VAAS), whi...
03/29/2020 ∙ by Jie Chen, et al. ∙ 20 ∙ share

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Automated discovery of a robust interatomic potential for aluminum

Atomistic molecular dynamics simulation is an important tool for predict...
03/10/2020 ∙ by Justin S. Smith, et al. ∙ 0 ∙ share

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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...
03/07/2020 ∙ by Jie Chen, et al. ∙ 15 ∙ share

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Asynchronous parallel adaptive stochastic gradient methods

Stochastic gradient methods (SGMs) are the predominant approaches to tra...
02/21/2020 ∙ by Yangyang Xu, et al. ∙ 0 ∙ share

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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...
02/12/2020 ∙ by Xiao Zang, et al. ∙ 17 ∙ share

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Linearly Convergent Algorithm with Variance Reduction for Distributed Stochastic Optimization

This paper considers a distributed stochastic strongly convex optimizati...
02/09/2020 ∙ by Jinlong Lei, et al. ∙ 0 ∙ share

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Convolution Neural Network Architecture Learning for Remote Sensing Scene Classification

Remote sensing image scene classification is a fundamental but challengi...
01/27/2020 ∙ by Jie Chen, et al. ∙ 7 ∙ share

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Embedding Compression with Isotropic Iterative Quantization

Continuous representation of words is a standard component in deep learn...
01/11/2020 ∙ by Siyu Liao, et al. ∙ 36 ∙ share

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Multitask learning over graphs

The problem of learning simultaneously several related tasks has receive...
01/07/2020 ∙ by Roula Nassif, et al. ∙ 0 ∙ share

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Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport

Hierarchical abstractions are a methodology for solving large-scale grap...
12/24/2019 ∙ by Tengfei Ma, et al. ∙ 12 ∙ share

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Chart Auto-Encoders for Manifold Structured Data

Auto-encoding and generative models have made tremendous successes in im...
12/20/2019 ∙ by Stefan Schonsheck, et al. ∙ 31 ∙ share

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A multi-label classification method using a hierarchical and transparent representation for paper-reviewer recommendation

Paper-reviewer recommendation task is of significant academic importance...
12/19/2019 ∙ by Dong Zhang, et al. ∙ 0 ∙ share

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CAG: A Real-time Low-cost Enhanced-robustness High-transferability Content-aware Adversarial Attack Generator

Deep neural networks (DNNs) are vulnerable to adversarial attack despite...
12/16/2019 ∙ by Huy Phan, et al. ∙ 11 ∙ share

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Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression

This paper presents a variational Bayesian kernel selection (VBKS) algor...
12/05/2019 ∙ by Tong Teng, et al. ∙ 28 ∙ share

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DFSMN-SAN with Persistent Memory Model for Automatic Speech Recognition

Self-attention networks (SAN) have been introduced into automatic speech...
10/28/2019 ∙ by Zhao You, et al. ∙ 0 ∙ share

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Adaptively Aligned Image Captioning via Adaptive Attention Time

Recent neural models for image captioning usually employs an encoder-dec...
09/19/2019 ∙ by Lun Huang, et al. ∙ 13 ∙ share

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Flexible, Fast and Accurate Densely-Sampled Light Field Reconstruction Network

The densely-sampled light field (LF) is highly desirable in various appl...
08/31/2019 ∙ by Jing Jin, et al. ∙ 0 ∙ share

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Attention on Attention for Image Captioning

Attention mechanisms are widely used in current encoder/decoder framewor...
08/19/2019 ∙ by Lun Huang, et al. ∙ 4 ∙ share

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Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics

Anti-money laundering (AML) regulations play a critical role in safeguar...
07/31/2019 ∙ by Mark Weber, et al. ∙ 0 ∙ share

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Learning High-fidelity Light Field Images From Hybrid Inputs

This paper explores the reconstruction of high-fidelity LF images (i.e.,...
07/23/2019 ∙ by Jing Jin, et al. ∙ 4 ∙ share

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Distributed Global Output-Feedback Control for a Class of Euler-Lagrange Systems

This published paper investigates the distributed tracking control probl...
06/29/2019 ∙ by Qingkai Yang, et al. ∙ 0 ∙ share

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Large Intelligent Surface/Antennas (LISA): Making Reflective Radios Smart

Large intelligent surface/antennas (LISA), a two-dimensional artificial ...
06/15/2019 ∙ by Ying-Chang Liang, et al. ∙ 0 ∙ share

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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...
05/16/2019 ∙ by Jun Wang, et al. ∙ 0 ∙ share

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IPC: A Benchmark Data Set for Learning with Graph-Structured Data

Benchmark data sets are an indispensable ingredient of the evaluation of...
05/15/2019 ∙ by Patrick Ferber, et al. ∙ 4 ∙ share

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Time Series Simulation by Conditional Generative Adversarial Net

Generative Adversarial Net (GAN) has been proven to be a powerful machin...
04/25/2019 ∙ by Rao Fu, et al. ∙ 0 ∙ share

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DAG-GNN: DAG Structure Learning with Graph Neural Networks

Learning a faithful directed acyclic graph (DAG) from samples of a joint...
04/22/2019 ∙ by Yue Yu, et al. ∙ 34 ∙ share

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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...
04/18/2019 ∙ by Chenyang Xi, et al. ∙ 24 ∙ share

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A Sequential Set Generation Method for Predicting Set-Valued Outputs

Consider a general machine learning setting where the output is a set of...
03/12/2019 ∙ by Tian Gao, et al. ∙ 2 ∙ share

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Stratified Labeling for Surface Consistent Parallax Correction and Occlusion Completion

The light field faithfully records the spatial and angular configuration...
03/07/2019 ∙ by Jie Chen, et al. ∙ 0 ∙ share

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EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Graph representation learning resurges as a trending research subject ow...
02/26/2019 ∙ by Aldo Pareja, et al. ∙ 20 ∙ share

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A laboratory-created dataset with ground-truth for hyperspectral unmixing evaluation

Spectral unmixing is an important and challenging problem in hyperspectr...
02/22/2019 ∙ by Min Zhao, et al. ∙ 14 ∙ share

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Scalable Graph Learning for Anti-Money Laundering: A First Look

Organized crime inflicts human suffering on a genocidal scale: the Mexic...
11/30/2018 ∙ by Mark Weber, et al. ∙ 0 ∙ share

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Adaptive Planner Scheduling with Graph Neural Networks

Automated planning is one of the foundational areas of AI. Since a singl...
11/01/2018 ∙ by Tengfei Ma, et al. ∙ 0 ∙ share

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Jie Chen

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