Search Results for author: Jie Chen

Found 146 papers, 46 papers with code

Transient Performance Analysis of the $\ell_1$-RLS

no code implementations14 Sep 2021 Wei Gao, Jie Chen, Cédric Richard, Wentao Shi, Qunfei Zhang

The recursive least-squares algorithm with $\ell_1$-norm regularization ($\ell_1$-RLS) exhibits excellent performance in terms of convergence rate and steady-state error in identification of sparse systems.

Supervised Linear Dimension-Reduction Methods: Review, Extensions, and Comparisons

no code implementations9 Sep 2021 Shaojie Xu, Joel Vaughan, Jie Chen, Agus Sudjianto, Vijayan Nair

Principal component analysis (PCA) is a well-known linear dimension-reduction method that has been widely used in data analysis and modeling.

Dimensionality Reduction

On Faster Convergence of Scaled Sign Gradient Descent

no code implementations4 Sep 2021 Xiuxian Li, Kuo-Yi Lin, Li Li, Yiguang Hong, Jie Chen

For the first two cases, it can be shown that the scaled signGD converges at a linear rate.

An Information Theory-inspired Strategy for Automatic Network Pruning

no code implementations19 Aug 2021 Xiawu Zheng, Yuexiao Ma, Teng Xi, Gang Zhang, Errui Ding, Yuchao Li, Jie Chen, Yonghong Tian, Rongrong Ji

This practically limits the application of model compression when the model needs to be deployed on a wide range of devices.

AutoML Model Compression +1

Attention-Guided NIR Image Colorization via Adaptive Fusion of Semantic and Texture Clues

no code implementations20 Jul 2021 Xingxing Yang, Jie Chen, Zaifeng Yang, Zhenghua Chen

Finally, a Fusion Attention Block (FAB) is proposed to adaptively fuse the features from the two branches and generate an optimized colorization result.

Colorization

Efficient proximal gradient algorithms for joint graphical lasso

no code implementations16 Jul 2021 Jie Chen, Ryosuke Shimmura, Joe Suzuki

We consider learning an undirected graphical model from sparse data.

CentripetalText: An Efficient Text Instance Representation for Scene Text Detection

no code implementations13 Jul 2021 Tao Sheng, Jie Chen, Zhouhui Lian

For the task of end-to-end scene text recognition, we outperform Mask TextSpotter v3 by 1. 1% on Total-Text.

Scene Text Scene Text Detection +1

Attention-Guided Progressive Neural Texture Fusion for High Dynamic Range Image Restoration

no code implementations13 Jul 2021 Jie Chen, Zaifeng Yang, Tsz Nam Chan, Hui Li, Junhui Hou, Lap-Pui Chau

A progressive texture blending module is designed to blend the encoded two-stream features in a multi-scale and progressive manner.

Image Restoration

Graph coarsening: From scientific computing to machine learning

no code implementations22 Jun 2021 Jie Chen, Yousef Saad, Zechen Zhang

The general method of graph coarsening or graph reduction has been a remarkably useful and ubiquitous tool in scientific computing and it is now just starting to have a similar impact in machine learning.

Discover Cross-Modality Nuances for Visible-Infrared Person Re-Identification

no code implementations CVPR 2021 Qiong Wu, Pingyang Dai, Jie Chen, Chia-Wen Lin, Yongjian Wu, Feiyue Huang, Bineng Zhong, Rongrong Ji

In this paper, we propose a joint Modality and Pattern Alignment Network (MPANet) to discover cross-modality nuances in different patterns for visible-infrared person Re-ID, which introduces a modality alleviation module and a pattern alignment module to jointly extract discriminative features.

Person Re-Identification

Scale-Consistent Fusion: from Heterogeneous Local Sampling to Global Immersive Rendering

no code implementations17 Jun 2021 Wenpeng Xing, Jie Chen, Zaifeng Yang, Qiang Wang

Image-based geometric modeling and novel view synthesis based on sparse, large-baseline samplings are challenging but important tasks for emerging multimedia applications such as virtual reality and immersive telepresence.

Novel View Synthesis Virtual Reality

Composition and Application of Current Advanced Driving Assistance System: A Review

no code implementations26 May 2021 Xinran Li, Kuo-Yi Lin, Min Meng, Xiuxian Li, Li Li, Yiguang Hong, Jie Chen

Due to the growing awareness of driving safety and the development of sophisticated technologies, advanced driving assistance system (ADAS) has been equipped in more and more vehicles with higher accuracy and lower price.

CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks

1 code implementation25 May 2021 Ruchir Puri, David S. Kung, Geert Janssen, Wei zhang, Giacomo Domeniconi, Vladimir Zolotov, Julian Dolby, Jie Chen, Mihir Choudhury, Lindsey Decker, Veronika Thost, Luca Buratti, Saurabh Pujar, Shyam Ramji, Ulrich Finkler, Susan Malaika, Frederick Reiss

In addition to its large scale, CodeNet has a rich set of high-quality annotations to benchmark and help accelerate research in AI techniques for a variety of critical coding tasks, including code similarity and classification, code translation between a large variety of programming languages, and code performance (runtime and memory) improvement techniques.

Code Classification Code Translation

Bias, Fairness, and Accountability with AI and ML Algorithms

no code implementations13 May 2021 Nengfeng Zhou, Zach Zhang, Vijayan N. Nair, Harsh Singhal, Jie Chen, Agus Sudjianto

In this paper, we provide an overview of bias and fairness issues that arise with the use of ML algorithms.

Fairness

Unsupervised domain adaptation via double classifiers based on high confidence pseudo label

no code implementations11 May 2021 Huihuang Chen, Li Li, Jie Chen, Kuo-Yi Lin

In addition to aligning the global distribution, the real domain adaptation should also align the meso distribution and the micro distribution.

Transfer Learning Unsupervised Domain Adaptation

Geometrical Characterization of Sensor Placement for Cone-Invariant and Multi-Agent Systems against Undetectable Zero-Dynamics Attacks

no code implementations10 May 2021 Jianqi Chen, Jieqiang Wei, Wei Chen, Henrik Sandberg, Karl H. Johansson, Jie Chen

Undetectable attacks are an important class of malicious attacks threatening the security of cyber-physical systems, which can modify a system's state but leave the system output measurements unaffected, and hence cannot be detected from the output.

RR-Net: Injecting Interactive Semantics in Human-Object Interaction Detection

no code implementations30 Apr 2021 Dongming Yang, Yuexian Zou, Can Zhang, Meng Cao, Jie Chen

Upon the frame, an Interaction Intensifier Module and a Correlation Parsing Module are carefully designed, where: a) interactive semantics from humans can be exploited and passed to objects to intensify interactions, b) interactive correlations among humans, objects and interactions are integrated to promote predictions.

Human-Object Interaction Detection

Graph Decoupling Attention Markov Networks for Semi-supervised Graph Node Classification

no code implementations28 Apr 2021 Jie Chen, Shouzhen Chen, Mingyuan Bai, Jian Pu, Junping Zhang, Junbin Gao

In this paper, we consider the label dependency of graph nodes and propose a decoupling attention mechanism to learn both hard and soft attention.

Classification General Classification +2

Underwater Target Recognition based on Multi-Decision LOFAR Spectrum Enhancement: A Deep Learning Approach

no code implementations26 Apr 2021 Jie Chen, Jie Liu, Chang Liu, Jian Zhang, Bing Han

To overcome this issue and to further improve the recognition performance, we adopt a deep learning approach for underwater target recognition and propose a LOFAR spectrum enhancement (LSE)-based underwater target recognition scheme, which consists of preprocessing, offline training, and online testing.

Carrying out CNN Channel Pruning in a White Box

1 code implementation24 Apr 2021 Yuxin Zhang, Mingbao Lin, Chia-Wen Lin, Jie Chen, Feiyue Huang, Yongjian Wu, Yonghong Tian, Rongrong Ji

Specifically, to model the contribution of each channel to differentiating categories, we develop a class-wise mask for each channel, implemented in a dynamic training manner w. r. t.

Classification Image Classification

Image-based Virtual Fitting Room

1 code implementation8 Apr 2021 Zhiling Huang, Junwen Bu, Jie Chen

We firstly used Mask R-CNN to find the regions of different fashion items, and secondly used Neural Style Transfer to change the style of the selected fashion items.

Style Transfer

CoLA: Weakly-Supervised Temporal Action Localization with Snippet Contrastive Learning

1 code implementation CVPR 2021 Can Zhang, Meng Cao, Dongming Yang, Jie Chen, Yuexian Zou

In this paper, we argue that learning by comparing helps identify these hard snippets and we propose to utilize snippet Contrastive learning to Localize Actions, CoLA for short.

Contrastive Learning Weakly Supervised Action Localization +2

Noise Injection-based Regularization for Point Cloud Processing

no code implementations28 Mar 2021 Xiao Zang, Yi Xie, Siyu Liao, Jie Chen, Bo Yuan

In this paper, we, for the first time, perform systematic investigation on noise injection-based regularization for point cloud-domain DNNs.

Data Augmentation Semantic Segmentation

Resilient Control under Quantization and Denial-of-Service: Co-designing a Deadbeat Controller and Transmission Protocol

no code implementations22 Mar 2021 Wenjie Liu, Jian Sun, Gang Wang, Francesco Bullo, Jie Chen

When both input and output channels are subject to DoS attacks and quantization, the proposed structure is shown able to decouple the encoding schemes for input, output, and estimated output signals.

Quantization

Linear Iterative Feature Embedding: An Ensemble Framework for Interpretable Model

no code implementations18 Mar 2021 Agus Sudjianto, Jinwen Qiu, Miaoqi Li, Jie Chen

The LIFE algorithm is able to fit a wide single-hidden-layer neural network (NN) accurately with three steps: defining the subsets of a dataset by the linear projections of neural nodes, creating the features from multiple narrow single-hidden-layer NNs trained on the different subsets of the data, combining the features with a linear model.

Projection-based QLP Algorithm for Efficiently Computing Low-Rank Approximation of Matrices

no code implementations12 Mar 2021 Maboud F. Kaloorazi, Jie Chen

The efficiency and effectiveness of our proposed PbP-QLP algorithm are investigated through various classes of synthetic and real-world data matrices.

Towards Unbiased COVID-19 Lesion Localisation and Segmentation via Weakly Supervised Learning

no code implementations1 Mar 2021 Yang Yang, Jiancong Chen, Ruixuan Wang, Ting Ma, Lingwei Wang, Jie Chen, Wei-Shi Zheng, Tong Zhang

Despite tremendous efforts, it is very challenging to generate a robust model to assist in the accurate quantification assessment of COVID-19 on chest CT images.

Performance of Domain-Wall Encoding for Quantum Annealing

no code implementations24 Feb 2021 Jie Chen, Tobias Stollenwerk, Nicholas Chancellor

In this paper we experimentally test the performance of the recently proposed domain-wall encoding of discrete variables from [Chancellor Quantum Sci.

Quantum Physics

Learning Structral coherence Via Generative Adversarial Network for Single Image Super-Resolution

1 code implementation25 Jan 2021 Yuanzhuo Li, Yunan Zheng, Jie Chen, Zhenyu Xu, Yiguang Liu

Among the major remaining challenges for single image super resolution (SISR) is the capacity to recover coherent images with global shapes and local details conforming to human vision system.

Image Restoration Image Super-Resolution

Generating a Doppelganger Graph: Resembling but Distinct

no code implementations23 Jan 2021 Yuliang Ji, Ru Huang, Jie Chen, Yuanzhe Xi

Deep generative models, since their inception, have become increasingly more capable of generating novel and perceptually realistic signals (e. g., images and sound waves).

Graph Representation Learning Node Classification

Discrete Graph Structure Learning for Forecasting Multiple Time Series

1 code implementation ICLR 2021 Chao Shang, Jie Chen, Jinbo Bi

Exploration of the correlation and causation among the variables in a multivariate time series shows promise in enhancing the performance of a time series model.

Time Series Time Series Forecasting

Transient Theoretical Analysis of Diffusion RLS Algorithm for Cyclostationary Colored Inputs

no code implementations12 Jan 2021 Wei Gao, Jie Chen, Cédric Richard

Convergence of the diffusion RLS (DRLS) algorithm to steady-state has been extensively studied in the literature, whereas no analysis of its transient convergence behavior has been reported yet.

A Plug-and-Play Priors Framework for Hyperspectral Unmixing

1 code implementation24 Dec 2020 Min Zhao, Xiuheng Wang, Jie Chen, Wei Chen

Spectral unmixing is a widely used technique in hyperspectral image processing and analysis.

Hyperspectral Unmixing Image Denoising

Empirical Evaluation of Typical Sparse Fast Fourier Transform Algorithms

no code implementations15 Dec 2020 Bin Li, Zhikang Jiang, Jie Chen

Computing the Sparse Fast Fourier Transform(sFFT) of a K-sparse signal of size N has emerged as a critical topic for a long time.

Online Convex Optimization Over Erdos-Renyi Random Networks

no code implementations NeurIPS 2020 Jinlong Lei, Peng Yi, Yiguang Hong, Jie Chen, Guodong Shi

The regret bounds scaling with respect to $T$ match those obtained by state-of-the-art algorithms and fundamental limits in the corresponding centralized online optimization problems, e. g., $\mathcal{O}(\sqrt{T}) $ and $\mathcal{O}(\ln(T)) $ regrets are established for convex and strongly convex losses with full gradient feedback and two-points information, respectively.

Handling Noisy Labels via One-Step Abductive Multi-Target Learning: An Application to Helicobacter Pylori Segmentation

no code implementations25 Nov 2020 Yongquan Yang, Yiming Yang, Jie Chen, Jiayi Zheng, Zhongxi Zheng

This situation raises two more difficult problems: 1) the methodology of approaches making corrections corresponding to potentially noisy-labeled instances has limitations due to the complex noise existing in labels; and 2) the appropriate evaluation strategy for validation/testing is unclear because of the great difficulty in collecting the noisy-free ground-truth labels.

Edge Adaptive Hybrid Regularization Model For Image Deblurring

no code implementations20 Nov 2020 Tingting Zhang, Jie Chen, Caiying Wu, Zhifei He, Tieyong Zeng, Qiyu Jin

In the proposed model, it detects the edges and then spatially adjusts the parameters of Tikhonov and TV regularization terms for each pixel according to the edge information.

Deblurring Image Restoration +1

On Performance of Sparse Fast Fourier Transform Algorithms Using the Aliasing Filter

no code implementations11 Nov 2020 Bin Li, Zhikang Jiang, Jie Chen

In the second part, we make two categories of experiments for computing the signals of different SNR, different N, different K by a standard testing platform and record the run time, percentage of the signal sampled and L0, L1, L2 error both in the exactly sparse case and general sparse case.

On Performance of Multiscale Sparse Fast Fourier Transform Algorithm

no code implementations11 Nov 2020 Bin Li, Zhikang Jiang, Jie Chen

The sFFT algorithms decrease the runtime and sampling complexity by taking advantage of the signal inherent characteristics that a large number of signals are sparse in the frequency domain(e. g., sensors, video data, audio, medical image, etc.).

Deep reinforcement learning for RAN optimization and control

no code implementations9 Nov 2020 Yu Chen, Jie Chen, Ganesh Krishnamurthi, Huijing Yang, Huahui Wang, Wenjie Zhao

Due to the high variability of the traffic in the radio access network (RAN), fixed network configurations are not flexible enough to achieve optimal performance.

Hyperspectral Unmixing via Nonnegative Matrix Factorization with Handcrafted and Learnt Priors

no code implementations9 Oct 2020 Min Zhao, Tiande Gao, Jie Chen, Wei Chen

In our work, we propose an NMF based unmixing framework which jointly uses a handcrafting regularizer and a learnt regularizer from data.

Hyperspectral Unmixing

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

no code implementations26 Sep 2020 Jing Jin, Junhui Hou, Zhiyu Zhu, Jie Chen, Sam Kwong

To preserve the parallax structure among the reconstructed SAIs, we subsequently append a consistency regularization network trained over a structure-aware loss function to refine the parallax relationships over the coarse estimation.

Disparity Estimation Super-Resolution

A deep learning-based approach for the automated surface inspection of copper clad laminate images

no code implementations19 Sep 2020 Xiaoqing Zheng, Jie Chen, Hongcheng Wang, Song Zheng, Yaguang Kong

A machine vision-based surface quality inspection system is usually composed of two processes: image acquisition and automatic defect detection.

Anomaly Detection Defect Detection

The 1st Tiny Object Detection Challenge:Methods and Results

1 code implementation16 Sep 2020 Xuehui Yu, Zhenjun Han, Yuqi Gong, Nan Jiang, Jian Zhao, Qixiang Ye, Jie Chen, Yuan Feng, Bin Zhang, Xiaodi Wang, Ying Xin, Jingwei Liu, Mingyuan Mao, Sheng Xu, Baochang Zhang, Shumin Han, Cheng Gao, Wei Tang, Lizuo Jin, Mingbo Hong, Yuchao Yang, Shuiwang Li, Huan Luo, Qijun Zhao, Humphrey Shi

The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection.

Human Detection Object Detection

Hyperspectral Image Super-Resolution via Deep Prior Regularization with Parameter Estimation

1 code implementation9 Sep 2020 Xiuheng Wang, Jie Chen, Qi Wei, Cédric Richard

Furthermore, the regularization parameter is simultaneously estimated to automatically adjust contribution of the physical model and {the} learned prior to reconstruct the final HR HSI.

Hyperspectral Image Super-Resolution Image Super-Resolution

Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms

no code implementations28 Jul 2020 Linwei Hu, Jie Chen, Vijayan N. Nair, Agus Sudjianto

Supervised Machine Learning (SML) algorithms, such as Gradient Boosting, Random Forest, and Neural Networks, have become popular in recent years due to their superior predictive performance over traditional statistical methods.

Supervised Machine Learning Techniques: An Overview with Applications to Banking

no code implementations28 Jul 2020 Linwei Hu, Jie Chen, Joel Vaughan, Hanyu Yang, Kelly Wang, Agus Sudjianto, Vijayan N. Nair

This article provides an overview of Supervised Machine Learning (SML) with a focus on applications to banking.

Deep Learning Methods for Solving Linear Inverse Problems: Research Directions and Paradigms

no code implementations27 Jul 2020 Yanna Bai, Wei Chen, Jie Chen, Weisi Guo

The linear inverse problem is fundamental to the development of various scientific areas.

Deep Spatial-angular Regularization for Compressive Light Field Reconstruction over Coded Apertures

1 code implementation ECCV 2020 Mantang Guo, Junhui Hou, Jing Jin, Jie Chen, Lap-Pui Chau

Coded aperture is a promising approach for capturing the 4-D light field (LF), in which the 4-D data are compressively modulated into 2-D coded measurements that are further decoded by reconstruction algorithms.

Image and Video Processing

Online Graph-Based Change Point Detection in Multiband Image Sequences

no code implementations24 Jun 2020 Ricardo Augusto Borsoi, Cédric Richard, André Ferrari, Jie Chen, José Carlos Moreira Bermudez

To effectively perform change-point detection in multitemporal images, it is important to devise techniques that are computationally efficient for processing large datasets, and that do not require knowledge about the nature of the changes.

Change Point Detection

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

1 code implementation18 Jun 2020 Zhiyu Zhu, Junhui Hou, Jie Chen, Huanqiang Zeng, Jiantao Zhou

Specifically, PZRes-Net learns a high resolution and \textit{zero-centric} residual image, which contains high-frequency spatial details of the scene across all spectral bands, from both inputs in a progressive fashion along the spectral dimension.

Hyperspectral Image Super-Resolution Hyperspectral Unmixing +1

Policy Gradient from Demonstration and Curiosity

no code implementations22 Apr 2020 Jie Chen, Wenjun Xu

In this work, an integrated policy gradient algorithm was proposed to boost exploration and facilitate intrinsic reward learning from only limited number of demonstrations.

Adaptive Explainable Neural Networks (AxNNs)

no code implementations5 Apr 2020 Jie Chen, Joel Vaughan, Vijayan N. Nair, Agus Sudjianto

While machine learning techniques have been successfully applied in several fields, the black-box nature of the models presents challenges for interpreting and explaining the results.

Distributed Computing

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

1 code implementation CVPR 2020 Jing Jin, Junhui Hou, Jie Chen, Sam Kwong

Light field (LF) images acquired by hand-held devices usually suffer from low spatial resolution as the limited sampling resources have to be shared with the angular dimension.

Super-Resolution

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

no code implementations CVPR 2020 Jie Chen, Zhiheng Li, Jiebo Luo, Chenliang Xu

Instead of blindly trusting quality-inconsistent PAs, WS^2 employs a learning-based selection to select effective PAs and a novel region integrity criterion as a stopping condition for weakly-supervised training.

Action Segmentation Semantic Segmentation +2

Asynchronous parallel adaptive stochastic gradient methods

1 code implementation21 Feb 2020 Yangyang Xu, Colin Sutcher-Shepard, Yibo Xu, Jie Chen

The proposed method is tested on both convex and non-convex machine learning problems, and the numerical results demonstrate its clear advantages over the sync counterpart.

Optimization and Control Distributed, Parallel, and Cluster Computing Numerical Analysis Numerical Analysis

Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models

1 code implementation12 Feb 2020 Xiao Zang, Yi Xie, Jie Chen, Bo Yuan

Worse, the bad actors found for one graph model severely compromise other models as well.

Graph Learning

Cooperative Pursuit with Multi-Pursuer and One Faster Free-moving Evader

1 code implementation IEEE Transactions on Cybernetics 2020 Xu Fang, Chen Wang, Lihua Xie, Jie Chen

When the faster evader is allowed to move freely without any constraint, the main issues are how to form an encirclement to trap the evader into the capture domain, how to balance between forming an encirclement and approaching the faster evader, and what conditions make the capture possible.

Systems and Control Systems and Control

Embedding Compression with Isotropic Iterative Quantization

no code implementations11 Jan 2020 Siyu Liao, Jie Chen, Yanzhi Wang, Qinru Qiu, Bo Yuan

Continuous representation of words is a standard component in deep learning-based NLP models.

Image Retrieval Quantization

Multitask learning over graphs: An Approach for Distributed, Streaming Machine Learning

no code implementations7 Jan 2020 Roula Nassif, Stefan Vlaski, Cedric Richard, Jie Chen, Ali H. Sayed

Multitask learning is an approach to inductive transfer learning (using what is learned for one problem to assist in another problem) and helps improve generalization performance relative to learning each task separately by using the domain information contained in the training signals of related tasks as an inductive bias.

Transfer Learning

Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks

2 code implementations27 Dec 2019 Huayan Guo, Ying-Chang Liang, Jie Chen, Erik G. Larsson

Our objective is to maximize the weighted sum-rate (WSR) of all users by joint designing the beamforming at the access point (AP) and the phase vector of the RIS elements, while both the perfect channel state information (CSI) setup and the imperfect CSI setup are investigated.

Signal Processing

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

1 code implementation24 Dec 2019 Tengfei Ma, Jie Chen

Both the coarsening matrix and the transport cost matrix are parameterized, so that an optimal coarsening strategy can be learned and tailored for a given set of graphs.

Graph Classification

Chart Auto-Encoders for Manifold Structured Data

no code implementations20 Dec 2019 Stefan Schonsheck, Jie Chen, Rongjie Lai

CAE admits desirable manifold properties that auto-encoders with a flat latent space fail to obey, predominantly proximity of data.

Representation Learning

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

no code implementations16 Dec 2019 Huy Phan, Yi Xie, Siyu Liao, Jie Chen, Bo Yuan

In addition, CAG exhibits high transferability across different DNN classifier models in black-box attack scenario by introducing random dropout in the process of generating perturbations.

Adversarial Attack

Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression

no code implementations5 Dec 2019 Tong Teng, Jie Chen, Yehong Zhang, Kian Hsiang Low

To achieve this, we represent the probabilistic kernel as an additional variational variable in a variational inference (VI) framework for SGPR models where its posterior belief is learned together with that of the other variational variables (i. e., inducing variables and kernel hyperparameters).

Stochastic Optimization Variational Inference

Graph Enhanced Cross-Domain Text-to-SQL Generation

no code implementations WS 2019 Siyu Huo, Tengfei Ma, Jie Chen, Maria Chang, Lingfei Wu, Michael Witbrock

Semantic parsing is a fundamental problem in natural language understanding, as it involves the mapping of natural language to structured forms such as executable queries or logic-like knowledge representations.

Natural Language Understanding Semantic Parsing +2

DFSMN-SAN with Persistent Memory Model for Automatic Speech Recognition

no code implementations28 Oct 2019 Zhao You, Dan Su, Jie Chen, Chao Weng, Dong Yu

Self-attention networks (SAN) have been introduced into automatic speech recognition (ASR) and achieved state-of-the-art performance owing to its superior ability in capturing long term dependency.

automatic-speech-recognition Large Vocabulary Continuous Speech Recognition +1

Adaptively Aligned Image Captioning via Adaptive Attention Time

1 code implementation NeurIPS 2019 Lun Huang, Wenmin Wang, Yaxian Xia, Jie Chen

In this paper, we propose a novel attention model, namely Adaptive Attention Time (AAT), to align the source and the target adaptively for image captioning.

Image Captioning

Deep Coarse-to-fine Dense Light Field Reconstruction with Flexible Sampling and Geometry-aware Fusion

1 code implementation31 Aug 2019 Jing Jin, Junhui Hou, Jie Chen, Huanqiang Zeng, Sam Kwong, Jingyi Yu

Specifically, the coarse sub-aperture image (SAI) synthesis module first explores the scene geometry from an unstructured sparsely-sampled LF and leverages it to independently synthesize novel SAIs, in which a confidence-based blending strategy is proposed to fuse the information from different input SAIs, giving an intermediate densely-sampled LF.

Depth Estimation Virtual Reality

Attention on Attention for Image Captioning

3 code implementations ICCV 2019 Lun Huang, Wenmin Wang, Jie Chen, Xiao-Yong Wei

In this paper, we propose an Attention on Attention (AoA) module, which extends the conventional attention mechanisms to determine the relevance between attention results and queries.

Image Captioning

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

1 code implementation31 Jul 2019 Mark Weber, Giacomo Domeniconi, Jie Chen, Daniel Karl I. Weidele, Claudio Bellei, Tom Robinson, Charles E. Leiserson

We contribute the Elliptic Data Set, a time series graph of over 200K Bitcoin transactions (nodes), 234K directed payment flows (edges), and 166 node features, including ones based on non-public data; to our knowledge, this is the largest labelled transaction data set publicly available in any cryptocurrency.

Time Series

Light Field Super-resolution via Attention-Guided Fusion of Hybrid Lenses

no code implementations23 Jul 2019 Jing Jin, Junhui Hou, Jie Chen, Sam Kwong, Jingyi Yu

To the best of our knowledge, this is the first end-to-end deep learning method for reconstructing a high-resolution LF image with a hybrid input.

Super-Resolution

Weighted Sum-Rate Optimization for Intelligent Reflecting Surface Enhanced Wireless Networks

2 code implementations20 May 2019 Huayan Guo, Ying-Chang Liang, Jie Chen, Erik G. Larsson

In addition, we consider a practical IRS assumption, in which the passive elements can only shift the incident signal to discrete phase levels.

Signal Processing

Learning discriminative features in sequence training without requiring framewise labelled data

no code implementations16 May 2019 Jun Wang, Dan Su, Jie Chen, Shulin Feng, Dongpeng Ma, Na Li, Dong Yu

We propose a novel method which simultaneously models both the sequence discriminative training and the feature discriminative learning within a single network architecture, so that it can learn discriminative deep features in sequence training that obviates the need for presegmented training data.

Time Series Simulation by Conditional Generative Adversarial Net

no code implementations25 Apr 2019 Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

Generative Adversarial Net (GAN) has been proven to be a powerful machine learning tool in image data analysis and generation.

Time Series

DAG-GNN: DAG Structure Learning with Graph Neural Networks

3 code implementations22 Apr 2019 Yue Yu, Jie Chen, Tian Gao, Mo Yu

Learning a faithful directed acyclic graph (DAG) from samples of a joint distribution is a challenging combinatorial problem, owing to the intractable search space superexponential in the number of graph nodes.

A Sequential Set Generation Method for Predicting Set-Valued Outputs

no code implementations12 Mar 2019 Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock

Though SSG is sequential in nature, it does not penalize the ordering of the appearance of the set elements and can be applied to a variety of set output problems, such as a set of classification labels or sequences.

General Classification Multi-Label Classification

Stratified Labeling for Surface Consistent Parallax Correction and Occlusion Completion

no code implementations7 Mar 2019 Jie Chen, Lap-Pui Chau, Junhui Hou

A stratified synthesis strategy is adopted which parses the scene content based on stratified disparity layers and across a varying range of spatial granularities.

Novel View Synthesis

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

5 code implementations26 Feb 2019 Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Tao B. Schardl, Charles E. Leiserson

Existing approaches typically resort to node embeddings and use a recurrent neural network (RNN, broadly speaking) to regulate the embeddings and learn the temporal dynamics.

Edge Classification General Classification +3

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

no code implementations22 Feb 2019 Min Zhao, Jie Chen, Zhe He

To the best of our knowledge, this dataset is the first publicly available dataset created in a systematic manner with ground-truth for spectral unmixing.

Hyperspectral Unmixing

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

2 code implementations30 Nov 2018 Mark Weber, Jie Chen, Toyotaro Suzumura, Aldo Pareja, Tengfei Ma, Hiroki Kanezashi, Tim Kaler, Charles E. Leiserson, Tao B. Schardl

Organized crime inflicts human suffering on a genocidal scale: the Mexican drug cartels have murdered 150, 000 people since 2006, upwards of 700, 000 people per year are "exported" in a human trafficking industry enslaving an estimated 40 million people.

Graph Learning

Automatic Seismic Salt Interpretation with Deep Convolutional Neural Networks

1 code implementation24 Nov 2018 Yu Zeng, Kebei Jiang, Jie Chen

One of the most crucial tasks in seismic reflection imaging is to identify the salt bodies with high precision.

Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability

2 code implementations14 Sep 2018 Lingfei Wu, Ian E. H. Yen, Jie Chen, Rui Yan

We thus propose the first analysis of RB from the perspective of optimization, which by interpreting RB as a Randomized Block Coordinate Descent in the infinite-dimensional space, gives a faster convergence rate compared to that of other random features.

Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders

1 code implementation NeurIPS 2018 Tengfei Ma, Jie Chen, Cao Xiao

We focus on the matrix representation of graphs and formulate penalty terms that regularize the output distribution of the decoder to encourage the satisfaction of validity constraints.

Time Series

Deep Learning for Generic Object Detection: A Survey

no code implementations6 Sep 2018 Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth, Jie Chen, Xinwang Liu, Matti Pietikäinen

Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined categories in natural images.

Object Proposal Generation

Fast Light Field Reconstruction With Deep Coarse-To-Fine Modeling of Spatial-Angular Clues

1 code implementation ECCV 2018 Henry Wing Fung Yeung, Junhui Hou, Jie Chen, Yuk Ying Chung, Xiaoming Chen

Specifically, our end-to-end model first synthesizes a set of intermediate novel sub-aperture images (SAIs) by exploring the coarse characteristics of the sparsely-sampled LF input with spatial-angular alternating convolutions.

Application of Machine Learning in Rock Facies Classification with Physics-Motivated Feature Augmentation

1 code implementation29 Aug 2018 Jie Chen, Yu Zeng

This paper shows the inclusion of physics-motivated feature interaction in feature augmentation can further improve the capability of machine learning in rock facies classification.

Classification Decision Making +3

Haze Density Estimation via Modeling of Scattering Coefficients of Iso-depth Regions

no code implementations19 Aug 2018 Jie Chen, Cheen-Hau Tan, Lap-Pui Chau

Vision based haze density estimation is of practical implications for the purpose of precaution alarm and emergency reactions toward disastrous hazy weathers.

Density Estimation

Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization

no code implementations14 Aug 2018 Gang Wang, Georgios B. Giannakis, Jie Chen

In this context, the problem of learning a two-layer ReLU network is approached in a binary classification setting, where the data are linearly separable and a hinge loss criterion is adopted.

Stochastic Gradient Descent with Biased but Consistent Gradient Estimators

1 code implementation31 Jul 2018 Jie Chen, Ronny Luss

The theory assumes that one can easily compute an unbiased gradient estimator, which is usually the case due to the sample average nature of empirical risk minimization.

Stochastic Optimization

SRN: Side-output Residual Network for Object Reflection Symmetry Detection and Beyond

1 code implementation17 Jul 2018 Wei Ke, Jie Chen, Jianbin Jiao, Guoying Zhao, Qixiang Ye

The end-to-end deep learning approach, referred to as a side-output residual network (SRN), leverages the output residual units (RUs) to fit the errors between the object ground-truth symmetry and the side-outputs of multiple stages.

Edge Detection Hand Pose Estimation +1

Explainable Neural Networks based on Additive Index Models

no code implementations5 Jun 2018 Joel Vaughan, Agus Sudjianto, Erind Brahimi, Jie Chen, Vijayan N. Nair

In this paper, we present the Explainable Neural Network (xNN), a structured neural network designed especially to learn interpretable features.

Feature Engineering

Locally Interpretable Models and Effects based on Supervised Partitioning (LIME-SUP)

no code implementations2 Jun 2018 Linwei Hu, Jie Chen, Vijayan N. Nair, Agus Sudjianto

This is in contrast with the KLIME approach that is based on clustering the predictor space.

Light Field Denoising via Anisotropic Parallax Analysis in a CNN Framework

no code implementations31 May 2018 Jie Chen, Junhui Hou, Lap-Pui Chau

Light field (LF) cameras provide perspective information of scenes by taking directional measurements of the focusing light rays.

Denoising

Ro-SOS: Metric Expression Network (MEnet) for Robust Salient Object Segmentation

1 code implementation15 May 2018 Delu Zeng, Yixuan He, Li Liu, Zhihong Chen, Jiabin Huang, Jie Chen, John Paisley

In this paper, we propose an end-to-end generic salient object segmentation model called Metric Expression Network (MEnet) to deal with saliency detection with the tolerance of distortion.

Saliency Detection Semantic Segmentation

Robust Video Content Alignment and Compensation for Clear Vision Through the Rain

no code implementations24 Apr 2018 Jie Chen, Cheen-Hau Tan, Junhui Hou, Lap-Pui Chau, He Li

Extensive evaluations show that advantage of up to 5dB is achieved on the scene restoration PSNR over state-of-the-art methods, and the advantage is especially obvious with highly complex and dynamic scenes.

Rain Removal

Robust Video Content Alignment and Compensation for Rain Removal in a CNN Framework

no code implementations CVPR 2018 Jie Chen, Cheen-Hau Tan, Junhui Hou, Lap-Pui Chau, He Li

Visual inspection shows that much cleaner rain removal is achieved especially for highly dynamic scenes with heavy and opaque rainfall from a fast moving camera.

Rain Removal

Texture Classification in Extreme Scale Variations using GANet

no code implementations13 Feb 2018 Li Liu, Jie Chen, Guoying Zhao, Paul Fieguth, Xilin Chen, Matti Pietikäinen

Because extreme scale variations are not necessarily present in most standard texture databases, to support the proposed extreme-scale aspects of texture understanding we are developing a new dataset, the Extreme Scale Variation Textures (ESVaT), to test the performance of our framework.

Classification General Classification +1

Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications

7 code implementations12 Feb 2018 Haowen Xu, Wenxiao Chen, Nengwen Zhao, Zeyan Li, Jiahao Bu, Zhihan Li, Ying Liu, Youjian Zhao, Dan Pei, Yang Feng, Jie Chen, Zhaogang Wang, Honglin Qiao

To ensure undisrupted business, large Internet companies need to closely monitor various KPIs (e. g., Page Views, number of online users, and number of orders) of its Web applications, to accurately detect anomalies and trigger timely troubleshooting/mitigation.

Unsupervised Anomaly Detection

From BoW to CNN: Two Decades of Texture Representation for Texture Classification

no code implementations31 Jan 2018 Li Liu, Jie Chen, Paul Fieguth, Guoying Zhao, Rama Chellappa, Matti Pietikainen

Texture is a fundamental characteristic of many types of images, and texture representation is one of the essential and challenging problems in computer vision and pattern recognition which has attracted extensive research attention.

General Classification Texture Classification

FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling

2 code implementations ICLR 2018 Jie Chen, Tengfei Ma, Cao Xiao

The graph convolutional networks (GCN) recently proposed by Kipf and Welling are an effective graph model for semi-supervised learning.

Node Classification

Solving Most Systems of Random Quadratic Equations

no code implementations NeurIPS 2017 Gang Wang, Georgios Giannakis, Yousef Saad, Jie Chen

For certain random measurement models, the proposed procedure returns the true solution $\bm{x}$ with high probability in time proportional to reading the data $\{(\bm{a}_i;y_i)\}_{1\le i \le m}$, provided that the number $m$ of equations is some constant $c>0$ times the number $n$ of unknowns, that is, $m\ge cn$.

Linear-Cost Covariance Functions for Gaussian Random Fields

1 code implementation16 Nov 2017 Jie Chen, Michael L. Stein

An essential ingredient of GRF is the covariance function that characterizes the joint Gaussian distribution of the field.

Methodology Numerical Analysis

Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications

no code implementations21 Oct 2017 Sijia Liu, Jie Chen, Pin-Yu Chen, Alfred O. Hero

In this paper, we design and analyze a new zeroth-order online algorithm, namely, the zeroth-order online alternating direction method of multipliers (ZOO-ADMM), which enjoys dual advantages of being gradient-free operation and employing the ADMM to accommodate complex structured regularizers.

Accurate Light Field Depth Estimation with Superpixel Regularization over Partially Occluded Regions

no code implementations7 Aug 2017 Jie Chen, Junhui Hou, Yun Ni, Lap-Pui Chau

Significant improvements have been made in terms of overall depth estimation error; however, current state-of-the-art methods still show limitations in handling intricate occluding structures and complex scenes with multiple occlusions.

Depth Estimation

On the Selective and Invariant Representation of DCNN for High-Resolution Remote Sensing Image Recognition

no code implementations4 Aug 2017 Jie Chen, Chao Yuan, Min Deng, Chao Tao, Jian Peng, Haifeng Li

Owing to its superiority in feature representation, DCNN has exhibited remarkable performance in scene recognition of high-resolution remote sensing (HRRS) images and classification of hyper-spectral remote sensing images.

Classification General Classification +1

RSI-CB: A Large Scale Remote Sensing Image Classification Benchmark via Crowdsource Data

1 code implementation30 May 2017 Haifeng Li, Xin Dou, Chao Tao, Zhixiang Hou, Jie Chen, Jian Peng, Min Deng, Ling Zhao

In this paper, we propose a remote sensing image classification benchmark (RSI-CB) based on massive, scalable, and diverse crowdsource data.

Classification General Classification +2

Solving Almost all Systems of Random Quadratic Equations

no code implementations29 May 2017 Gang Wang, Georgios B. Giannakis, Yousef Saad, Jie Chen

This paper deals with finding an $n$-dimensional solution $x$ to a system of quadratic equations of the form $y_i=|\langle{a}_i, x\rangle|^2$ for $1\le i \le m$, which is also known as phase retrieval and is NP-hard in general.

What do We Learn by Semantic Scene Understanding for Remote Sensing imagery in CNN framework?

no code implementations19 May 2017 Haifeng Li, Jian Peng, Chao Tao, Jie Chen, Min Deng

Is the DCNN recognition mechanism centered on object recognition still applicable to the scenarios of remote sensing scene understanding?

Object Recognition Scene Recognition +1

Adaptation and learning over networks for nonlinear system modeling

no code implementations28 Apr 2017 Simone Scardapane, Jie Chen, Cédric Richard

In this chapter, we analyze nonlinear filtering problems in distributed environments, e. g., sensor networks or peer-to-peer protocols.

SRN: Side-output Residual Network for Object Symmetry Detection in the Wild

1 code implementation CVPR 2017 Wei Ke, Jie Chen, Jianbin Jiao, Guoying Zhao, Qixiang Ye

By stacking RUs in a deep-to-shallow manner, SRN exploits the 'flow' of errors among multiple scales to ease the problems of fitting complex outputs with limited layers, suppressing the complex backgrounds, and effectively matching object symmetry of different scales.

Symmetry Detection

Multitask diffusion adaptation over networks with common latent representations

no code implementations13 Feb 2017 Jie Chen, Cédric Richard, Ali H. Sayed

Online learning with streaming data in a distributed and collaborative manner can be useful in a wide range of applications.

Sparse Phase Retrieval via Truncated Amplitude Flow

1 code implementation23 Nov 2016 Gang Wang, Liang Zhang, Georgios B. Giannakis, Mehmet Akcakaya, Jie Chen

Upon formulating sparse PR as an amplitude-based nonconvex optimization task, SPARTA works iteratively in two stages: In stage one, the support of the underlying sparse signal is recovered using an analytically well-justified rule, and subsequently, a sparse orthogonality-promoting initialization is obtained via power iterations restricted on the support; and, in the second stage, the initialization is successively refined by means of hard thresholding based gradient-type iterations.

Information Theory Information Theory Optimization and Control

Self-learning Scene-specific Pedestrian Detectors using a Progressive Latent Model

no code implementations CVPR 2017 Qixiang Ye, Tianliang Zhang, Qiang Qiu, Baochang Zhang, Jie Chen, Guillermo Sapiro

In this paper, a self-learning approach is proposed towards solving scene-specific pedestrian detection problem without any human' annotation involved.

Object Discovery Object Localization +2

Solving Large-scale Systems of Random Quadratic Equations via Stochastic Truncated Amplitude Flow

no code implementations29 Oct 2016 Gang Wang, Georgios B. Giannakis, Jie Chen

A novel approach termed \emph{stochastic truncated amplitude flow} (STAF) is developed to reconstruct an unknown $n$-dimensional real-/complex-valued signal $\bm{x}$ from $m$ `phaseless' quadratic equations of the form $\psi_i=|\langle\bm{a}_i,\bm{x}\rangle|$.

On Bochner's and Polya's Characterizations of Positive-Definite Kernels and the Respective Random Feature Maps

no code implementations27 Oct 2016 Jie Chen, Dehua Cheng, Yan Liu

A well-known construction of such functions comes from Bochner's characterization, which connects a positive-definite function with a probability distribution.

Gaussian Processes

Light Field Compression with Disparity Guided Sparse Coding based on Structural Key Views

no code implementations12 Oct 2016 Jie Chen, Junhui Hou, Lap-Pui Chau

Recent imaging technologies are rapidly evolving for sampling richer and more immersive representations of the 3D world.

Saliency Integration: An Arbitrator Model

no code implementations4 Aug 2016 Yingyue Xu, Xiaopeng Hong, Fatih Porikli, Xin Liu, Jie Chen, Guoying Zhao

Previous offline integration methods usually face two challenges: 1. if most of the candidate saliency models misjudge the saliency on an image, the integration result will lean heavily on those inferior candidate models; 2. an unawareness of the ground truth saliency labels brings difficulty in estimating the expertise of each candidate model.

Hierarchically Compositional Kernels for Scalable Nonparametric Learning

no code implementations2 Aug 2016 Jie Chen, Haim Avron, Vikas Sindhwani

We propose a novel class of kernels to alleviate the high computational cost of large-scale nonparametric learning with kernel methods.

Stochastic Behavior of the Nonnegative Least Mean Fourth Algorithm for Stationary Gaussian Inputs and Slow Learning

no code implementations24 Aug 2015 Jingen Ni, Jian Yang, Jie Chen, Cédric Richard, José Carlos M. Bermudez

Some system identification problems impose nonnegativity constraints on the parameters to estimate due to inherent physical characteristics of the unknown system.

Parallel Gaussian Process Regression for Big Data: Low-Rank Representation Meets Markov Approximation

no code implementations17 Nov 2014 Kian Hsiang Low, Jiangbo Yu, Jie Chen, Patrick Jaillet

To improve its scalability, this paper presents a low-rank-cum-Markov approximation (LMA) of the GP model that is novel in leveraging the dual computational advantages stemming from complementing a low-rank approximate representation of the full-rank GP based on a support set of inputs with a Markov approximation of the resulting residual process; the latter approximation is guaranteed to be closest in the Kullback-Leibler distance criterion subject to some constraint and is considerably more refined than that of existing sparse GP models utilizing low-rank representations due to its more relaxed conditional independence assumption (especially with larger data).

Symmetric low-rank representation for subspace clustering

no code implementations31 Oct 2014 Jie Chen, Haixian Zhang, Hua Mao, Yongsheng Sang, Zhang Yi

We propose a symmetric low-rank representation (SLRR) method for subspace clustering, which assumes that a data set is approximately drawn from the union of multiple subspaces.

Decentralized Data Fusion and Active Sensing with Mobile Sensors for Modeling and Predicting Spatiotemporal Traffic Phenomena

no code implementations9 Aug 2014 Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan, Ali Oran, Patrick Jaillet, John Dolan, Gaurav Sukhatme

The problem of modeling and predicting spatiotemporal traffic phenomena over an urban road network is important to many traffic applications such as detecting and forecasting congestion hotspots.

Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations

no code implementations9 Aug 2014 Jie Chen, Nannan Cao, Kian Hsiang Low, Ruofei Ouyang, Colin Keng-Yan Tan, Patrick Jaillet

We theoretically guarantee the predictive performances of our proposed parallel GPs to be equivalent to that of some centralized approximate GP regression methods: The computation of their centralized counterparts can be distributed among parallel machines, hence achieving greater time efficiency and scalability.

Gaussian Processes

GP-Localize: Persistent Mobile Robot Localization using Online Sparse Gaussian Process Observation Model

no code implementations21 Apr 2014 Nuo Xu, Kian Hsiang Low, Jie Chen, Keng Kiat Lim, Etkin Baris Ozgul

Central to robot exploration and mapping is the task of persistent localization in environmental fields characterized by spatially correlated measurements.

Subspace clustering using a symmetric low-rank representation

no code implementations7 Mar 2014 Jie Chen, Hua Mao, Yongsheng Sang, Zhang Yi

In this paper, we propose a low-rank representation with symmetric constraint (LRRSC) method for robust subspace clustering.

Steady-state performance of non-negative least-mean-square algorithm and its variants

no code implementations24 Jan 2014 Jie Chen, José Carlos M. Bermudez, Cédric Richard

The transient behavior of the NNLMS, Normalized NNLMS, Exponential NNLMS and Sign-Sign NNLMS algorithms have been studied in our previous work.

Convergence analysis of kernel LMS algorithm with pre-tuned dictionary

no code implementations31 Oct 2013 Jie Chen, Wei Gao, Cédric Richard, Jose-Carlos M. Bermudez

In addition to choosing a reproducing kernel and setting filter parameters, designing a KLMS adaptive filter requires to select a so-called dictionary in order to get a finite-order model.

Nonlinear unmixing of hyperspectral images using a semiparametric model and spatial regularization

no code implementations31 Oct 2013 Jie Chen, Cédric Richard, Alfred O. Hero III

Incorporating spatial information into hyperspectral unmixing procedures has been shown to have positive effects, due to the inherent spatial-spectral duality in hyperspectral scenes.

Hyperspectral Unmixing

Online dictionary learning for kernel LMS. Analysis and forward-backward splitting algorithm

no code implementations22 Jun 2013 Wei Gao, Jie Chen, Cédric Richard, Jianguo Huang

Unfortunately, an undesirable characteristic of these methods is that the order of the filters grows linearly with the number of input data.

Dictionary Learning

Gaussian Process-Based Decentralized Data Fusion and Active Sensing for Mobility-on-Demand System

no code implementations2 Jun 2013 Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan

This paper presents a novel decentralized data fusion and active sensing algorithm for real-time, fine-grained mobility demand sensing and prediction with a fleet of autonomous robotic vehicles in a MoD system.

Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations

no code implementations24 May 2013 Jie Chen, Nannan Cao, Kian Hsiang Low, Ruofei Ouyang, Colin Keng-Yan Tan, Patrick Jaillet

We theoretically guarantee the predictive performances of our proposed parallel GPs to be equivalent to that of some centralized approximate GP regression methods: The computation of their centralized counterparts can be distributed among parallel machines, hence achieving greater time efficiency and scalability.

Gaussian Processes

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